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Stock analysis, valuation models, portfolio optimization, earnings breakdowns, investment research, financial statements, tax planning, DCF modeling. Deliverables as interactive dashboards, PDF reports, and Excel models. Tags: latest:1.0.17 Version history: v1.0.17 | 2026-08-24T02:01:15.938Z | user Content updat","descriptionLabel":"Technical summary","evidenceSummary":"Capability contract not published. No trust telemetry is available yet. 5.6K downloads reported by the source. 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Stock analysis, valuation models, portfolio optimization, earnings breakdowns, investment research, financial statements, tax planning, DCF modeling. Deliverables as interactive dashboards, PDF reports, and Excel models.\n\nTags: latest:1.0.17\n\nVersion history:\n\nv1.0.17 | 2026-08-24T02:01:15.938Z | user\n\nContent updated.\n\nv1.0.16 | 2026-08-24T01:45:34.970Z | user\n\nContent updated.\n\nv1.0.15 | 2026-08-03T06:05:58.296Z | user\n\nContent updated.\n\nv1.0.14 | 2026-08-02T20:46:45.778Z | user\n\nDisplay title updated.\n\nv1.0.13 | 2026-07-17T03:42:13.283Z | auto\n\n- Skill renamed from \"fin-cog\" to \"stock-analysis-cellcog\".\n- Documentation updated to reflect the new skill name throughout.\n- Removed the obsolete \"skill-card.md\" file.\n- No changes to core functionality or requirements.\n\nv1.0.12 | 2026-04-23T06:18:53.825Z | auto\n\nfin-cog 1.0.12\n\n- Added requirements for Python 3 and the CELLCOG_API_KEY environment variable in metadata.\n- No other functional or documentation changes.\n\nv1.0.11 | 2026-04-14T17:32:18.069Z | auto\n\n- Updated the skill description to streamline deliverable formats and clarify offerings.\n- Improved the usage instructions for clarity, especially distinguishing between agent types.\n- No changes to core logic—documentation update only.\n\nv1.0.10 | 2026-04-13T01:00:48.992Z | auto\n\n- Updated the description to emphasize AI capabilities, deliverable types, and CellCog's DeepResearch Bench ranking.\n- Added an import statement for `CellCogClient` to the \"How to Use\" example for enhanced clarity.\n- Expanded the description of deliverables and features in the opening summary.\n- No changes to core features or functionality — documentation/content updates only.\n\nv1.0.9 | 2026-04-12T23:35:27.296Z | auto\n\n- Simplified and clarified the skill description for easier reading and a more direct explanation of key features.\n- Shortened and streamlined the \"How to Use\" section; emphasized prompt usage and essential SDK references.\n- Condensed instructions for various agent platforms, improving clarity for different workflows.\n- Removed repetitive and overly detailed explanations, focusing on concise examples and common use cases.\n- Kept all functional details and example prompts, preserving demonstration of analysis and deliverable options.\n- No changes to functionality—this is a significant documentation and usability improvement.\n\nv1.0.8 | 2026-04-08T05:58:00.007Z | auto\n\n- Major rewrite of the SKILL.md documentation for clarity, depth, and real-world examples.\n- Expanded usage scenarios and detailed prompt examples for stock analysis, portfolio optimization, financial modeling, reporting, and personal finance.\n- Clearly described available output formats (HTML dashboard, PDF, XLSX, Markdown) and recommendations for each.\n- Refined and expanded Chat Mode guidance for different types of financial analysis tasks.\n- Updated summary to showcase Wall Street-grade capabilities and #1 ranking on DeepResearch Bench (Apr 2026).\n\nv1.0.7 | 2026-04-06T05:07:13.072Z | auto\n\n- Simplified and clarified the skill description for easier understanding.\n- Trimmed and restructured SKILL.md, focusing on core use cases and capabilities.\n- Added a concise feature list under \"What CellCog Has Internally\" for quick reference.\n- Streamlined guidance on agent modes and related skills.\n- Removed extensive prompt examples and long explanations for brevity.\n\nv1.0.6 | 2026-04-03T01:43:32.050Z | auto\n\nfin-cog 1.0.6 changelog\n\n- Added example code for OpenClaw agents using the notify_session_key parameter for better support of fire-and-forget (long-running) financial tasks.\n- Clarified SDK usage, distinguishing OpenClaw agents from others with separate code examples.\n- Updated prerequisite instructions and code blocks for more accurate and user-friendly guidance.\n- Minor refinements to documentation flow for clarity and usability.\n\nv1.0.5 | 2026-04-03T00:07:49.060Z | auto\n\n**Changelog for fin-cog v1.0.5**\n\n- Updated SKILL.md to simplify and clarify SDK usage instructions.\n- Replaced the code example with a more concise \"Quick start\" snippet.\n- Added explicit guidance to reference the cellcog skill for advanced API options and deeper documentation.\n- Minor editorial cleanups and section reorganizations to improve readability for new users.\n\nv1.0.4 | 2026-04-02T03:33:48.059Z | auto\n\n- Updated DeepResearch Bench ranking from \"Feb 2026\" to \"Apr 2026\" in the description and introduction.\n- No functional or API changes; documentation wording only.\n\nv1.0.3 | 2026-03-27T04:17:22.631Z | auto\n\n- Improved and clarified the skill description for easier understanding.\n- Added platform metadata specifying support for Darwin, Linux, and Windows.\n- Included a homepage link for further information.\n- No changes to code or functionality; documentation updates only.\n\nv1.0.2 | 2026-03-19T02:53:27.379Z | user\n\nfin-cog 1.0.2\n\n- Added new \"agent team max\" chat mode for high-stakes financial work, such as M&A due diligence and institutional-grade research.\n- Updated \"Chat Mode for Finance\" table and section to include guidance for \"agent team max\" (requires ≥2,000 credits).\n- Clarified mode selection: use \"agent team\" for deep analysis, and \"agent\" for quick lookups; added advice for when to use \"agent team max\".\n- No changes to core capabilities, examples, or prerequisites.\n\nv1.0.1 | 2026-02-11T01:42:04.388Z | user\n\nfin-cog 1.0.1\n\n- Added author field (\"CellCog\") and dependencies ([cellcog]) to skill metadata.\n- Clarified prerequisite by renaming \"CellCog mothership skill\" to \"`cellcog` skill\".\n- No changes to core functionality or features.\n\nv1.0.0 | 2026-02-08T00:43:31.985Z | user\n\nInitial release of fin-cog: Wall Street-grade financial analysis for everyone.\n\n- Provides advanced financial analysis: stock deep dives, valuation models, portfolio optimization, earnings breakdowns, financial statements, tax planning, and more.\n- Integrates state-of-the-art financial models and ranks #1 on DeepResearch Bench (Feb 2026).\n- Supports a wide range of deliverables: interactive HTML dashboards, PDF reports, Excel models, and Markdown.\n- Designed for use with the CellCog skill for setup and API calls.\n- Includes extensive documentation, examples, prompt patterns, and guidance for both deep and quick financial tasks.\n\nArchive index:\n\nArchive v1.0.17: 3 files, 5927 bytes\n\nFiles: skill-card.md (2323b), SKILL.md (9401b), _meta.json (142b)\n\nFile v1.0.17:SKILL.md\n\n---\nname: stock-analysis-cellcog\ndescription: \"AI financial analysis and stock research powered by CellCog. Stock analysis, valuation models, portfolio optimization, earnings breakdowns, investment research, financial statements, tax planning, DCF modeling. Deliverables as interactive dashboards, PDF reports, and Excel models.\"\nmetadata:\n  openclaw:\n    emoji: \"💰\"\n    os: [darwin, linux, windows]\n    requires:\n      bins: [python3]\n      env: [CELLCOG_API_KEY]\nauthor: CellCog\nhomepage: https://cellcog.ai\ndependencies: [cellcog]\n---\n# Stock Analysis - Wall Street-Grade Analysis, Accessible Globally\n\n**Wall Street-grade analysis, accessible globally.** Deep financial reasoning powered by #1 on DeepResearch Bench (Apr 2026) + SOTA financial models.\n\nThe best financial analysis has always lived behind Bloomberg terminals, institutional research desks, and $500/hour consultants. CellCog brings that same depth — stock analysis, valuation models, portfolio optimization, earnings breakdowns — to anyone with a prompt. From raw tickers to boardroom-ready deliverables in one request.\n\n## How to Use\n\nFor your first CellCog task in a session, read the **cellcog** skill for the full SDK reference — file handling, chat modes, timeouts, and more.\n\n**OpenClaw (fire-and-forget):**\n```python\nresult = client.create_chat(\n    prompt=\"[your task prompt]\",\n    notify_session_key=\"agent:main:main\",\n    task_label=\"my-task\",\n    chat_mode=\"team\",\n)\n```\n\n**All agents except OpenClaw (blocks until done):**\n```python\nfrom cellcog import CellCogClient\nclient = CellCogClient(agent_provider=\"openclaw|cursor|claude-code|codex|...\")\nresult = client.create_chat(\n    prompt=\"[your task prompt]\",\n    task_label=\"my-task\",\n    chat_mode=\"team\",\n)\nprint(result[\"message\"])\n```\n\n\n---\n\n## What Financial Work You Can Do\n\n### Stock & Equity Analysis\n\nDeep dives into public companies:\n\n- **Company Analysis**: \"Analyze NVIDIA — revenue trends, margins, competitive moat, and forward guidance\"\n- **Earnings Breakdowns**: \"Break down Apple's Q4 2025 earnings — beat/miss, segment performance, management commentary\"\n- **Valuation Models**: \"Build a DCF model for Microsoft with bear, base, and bull scenarios\"\n- **Peer Comparisons**: \"Compare semiconductor stocks — NVDA, AMD, INTC, TSM — on valuation, growth, and profitability metrics\"\n- **Technical Analysis**: \"Analyze Tesla's price action — key support/resistance levels, moving averages, and volume trends\"\n\n**Example prompt:**\n> \"Create a comprehensive stock analysis for Palantir (PLTR):\n> \n> Cover:\n> - Business model and revenue breakdown (government vs commercial)\n> - Last 4 quarters earnings performance\n> - Key financial metrics (P/E, P/S, FCF margin, revenue growth)\n> - Competitive positioning vs Snowflake, Databricks, C3.ai\n> - Bull and bear thesis\n> - Valuation assessment\n> \n> Deliver as an interactive HTML report with charts.\"\n\n### Portfolio Analysis & Optimization\n\nManage and optimize investments:\n\n- **Portfolio Review**: \"Analyze my portfolio: 40% AAPL, 20% MSFT, 15% GOOGL, 15% AMZN, 10% TSLA — diversification, risk, and recommendations\"\n- **Asset Allocation**: \"Design an optimal portfolio for a 35-year-old with $200K, moderate risk tolerance\"\n- **Risk Assessment**: \"Calculate the Sharpe ratio, beta, and maximum drawdown for this portfolio over the last 3 years\"\n- **Rebalancing**: \"My portfolio drifted from target — recommend rebalancing trades to minimize tax impact\"\n\n### Financial Modeling\n\nBuild professional financial models:\n\n- **DCF Models**: \"Build a discounted cash flow model for Shopify with sensitivity analysis on growth and discount rate\"\n- **Startup Financial Models**: \"Create a 3-year financial projection for a B2B SaaS with $50K MRR growing 15% monthly\"\n- **LBO Models**: \"Model a leveraged buyout scenario for a $100M revenue company at 8x EBITDA\"\n- **Scenario Analysis**: \"Create a 3-scenario model (recession, baseline, boom) for a retail REIT portfolio\"\n\n### Financial Documents & Reports\n\nProfessional financial deliverables:\n\n- **Investment Memos**: \"Write an investment memo recommending a position in CrowdStrike\"\n- **Quarterly Reports**: \"Create a quarterly financial report for my small business\"\n- **Financial Statements**: \"Generate pro forma financial statements for a startup fundraise\"\n- **Tax Planning**: \"Analyze tax optimization strategies for a freelancer earning $150K with $30K in capital gains\"\n\n### Personal Finance\n\nEveryday financial planning:\n\n- **Retirement Planning**: \"How much do I need to save monthly to retire at 55 with $2M? I'm 30, saving $2K/month currently\"\n- **Mortgage Analysis**: \"Compare a 15-year vs 30-year mortgage on a $500K home with 20% down at current rates\"\n- **Debt Payoff**: \"Create a debt payoff plan: $15K student loans at 5%, $8K credit card at 22%, $25K car loan at 6%\"\n- **Budget Optimization**: \"Analyze my spending breakdown and recommend where to cut to save $1,000/month more\"\n\n---\n\n## Output Formats\n\nCellCog delivers financial analysis in multiple formats:\n\n| Format | Best For |\n|--------|----------|\n| **Interactive HTML Dashboard** | Explorable charts, drill-down analysis, live data presentation |\n| **PDF Report** | Shareable, printable investment memos and reports |\n| **XLSX Spreadsheet** | Editable financial models, projections, calculations |\n| **Markdown** | Quick analysis for integration into your docs |\n\nSpecify your preferred format in the prompt:\n- \"Deliver as an interactive HTML report with charts\"\n- \"Create a PDF investment memo\"\n- \"Build this as an editable Excel model\"\n\n---\n\n## Choosing Mode & Tier\n\n**Use `chat_mode=\"team\"` — this is exactly what Agent Team exists for.** Deep research is THE Team use case: multi-source synthesis, cross-validation, citation verification, multiple reasoning passes.\n\n| Scenario | Recommended |\n|----------|-------------|\n| Deep financial analysis, valuation models, multi-company comparisons | `chat_mode=\"team\"` (default tier `\"core\"`) |\n| M&A due diligence, high-stakes investment decisions | `chat_mode=\"team\", chat_tier=\"max\"` (requires >=2,000 credits) |\n| Quick lookups, simple summaries | `chat_mode=\"agent\"` |\n\nLegacy names `\"agent team\"` / `\"agent team max\"` still work forever (they map to team core / team max).\n\n---\n\n## Example Prompts\n\n**Comprehensive stock analysis:**\n> \"Create a full investment analysis for AMD:\n> \n> 1. Business Overview — segments, revenue mix, competitive positioning\n> 2. Financial Performance — last 8 quarters revenue, margins, EPS trends\n> 3. Valuation — P/E, P/S, PEG vs peers (NVDA, INTC, QCOM)\n> 4. Growth Catalysts — AI/datacenter, gaming, embedded\n> 5. Risk Factors — competition, cyclicality, customer concentration\n> 6. Bull/Bear/Base price targets\n> \n> Interactive HTML report with comparison charts.\"\n\n**Financial model:**\n> \"Build a startup financial model:\n> \n> Business: B2B SaaS, project management tool\n> Current: $30K MRR, 200 customers, $150 ARPU\n> Growth: 12% MoM for 12 months, then 8% for next 12\n> Team: 8 people now, hiring 4 in next year\n> Expenses: $180K/month burn rate\n> \n> Create a 24-month projection showing:\n> - Revenue forecast with cohort analysis\n> - Expense breakdown and hiring plan\n> - Cash flow and runway\n> - Unit economics (CAC, LTV, payback period)\n> - Break-even analysis\n> \n> Deliver as Excel spreadsheet with charts.\"\n\n**Personal finance:**\n> \"I'm 28, earning $120K/year in San Francisco. I want to:\n> 1. Max out 401K contributions\n> 2. Build a 6-month emergency fund ($30K)\n> 3. Save for a house down payment ($100K in 5 years)\n> 4. Start investing in index funds\n> \n> Create a detailed monthly financial plan that shows how to prioritize these goals with my take-home pay after taxes. Include a timeline and visual roadmap.\"\n\n**Earnings analysis:**\n> \"Break down Tesla's most recent quarterly earnings:\n> \n> - Revenue vs estimates (beat/miss by how much?)\n> - Automotive margins — trend over last 4 quarters\n> - Energy and services segment performance\n> - Key quotes from management on guidance\n> - What analysts are saying post-earnings\n> - Bull and bear reactions\n> \n> Deliver as a concise PDF report with charts.\"\n\n---\n\n## Tips for Better Financial Analysis\n\n1. **Be specific about metrics**: \"Revenue growth\" is vague. \"YoY revenue growth for the last 8 quarters with segment breakdown\" is precise.\n\n2. **Specify time horizons**: \"Analyze AAPL\" is open-ended. \"Analyze AAPL's performance and outlook for the next 12 months\" is actionable.\n\n3. **State your purpose**: \"For an investment decision\", \"For a board presentation\", \"For personal planning\" — context shapes the analysis.\n\n4. **Include constraints**: Budget, risk tolerance, time horizon, tax situation — these matter for financial recommendations.\n\n5. **Request scenarios**: \"Include bear, base, and bull cases\" gives you a range, not just a point estimate.\n\n6. **Ask for the deliverable you need**: \"Interactive dashboard\", \"PDF memo\", \"Excel model\" — specify the format for the best result.\n\n---\n\n## If CellCog is not installed\n\n**Claude Code, Cursor, Codex + 70 more agents:** `npx skills add cellcog/skills --skill cellcog`\n**OpenClaw:** `openclaw skills install @cellcog/cellcog`\n**CellCog plugin users:** run `/cellcog-setup` (or `/cellcog:cellcog-setup` depending on your tool)\n**Manual setup:** `pip install -U cellcog` and set `CELLCOG_API_KEY`. See the **cellcog** skill for SDK reference.\n\nFile v1.0.17:_meta.json\n\n{\n  \"ownerId\": \"kn7a96cj9q65e0bhmzahv790en80ffqm\",\n  \"slug\": \"stock-analysis-cellcog\",\n  \"version\": \"1.0.17\",\n  \"publishedAt\": 1787536875938\n}\n\nFile v1.0.17:skill-card.md\n\n## Description:\n\nStock Analysis helps agents use CellCog for stock research, valuation models, portfolio optimization, earnings breakdowns, investment research, financial statements, tax planning, DCF modeling, and deliverables such as dashboards, PDF reports, and Excel models.\n\nThis skill is ready for commercial/non-commercial use.\n\n## Publisher:\n\n[cellcog](https://clawhub.ai/user/cellcog)\n\n### License/Terms of Use:\n\nMIT-0\n\n## Use Case:\n\nExternal users and developers use this skill to request CellCog-powered financial research, stock analysis, portfolio analysis, financial models, and finance-focused reports from an agent.\n\n### Deployment Geography for Use:\n\nGlobal\n\n## Known Risks and Mitigations:\n\nRisk: Financial prompts, portfolio details, and related context may be sent to a third-party service.\n\nMitigation: Install only if CellCog is trusted, avoid unnecessary sensitive records, and use a restricted, rotatable CELLCOG_API_KEY.\n\nRisk: The skill provides financial, tax, legal, or investment-oriented outputs that may be incorrect or unsuitable for a user's situation.\n\nMitigation: Treat outputs as informational and require qualified human review before making financial, tax, legal, or investment decisions.\n\nRisk: Mutable install instructions can change what code or package version is installed.\n\nMitigation: Prefer a pinned, verified package or skill version before deployment.\n\n## Reference(s):\n\n- [CellCog Homepage](https://cellcog.ai)\n- [ClawHub Skill Page](https://clawhub.ai/cellcog/skills/stock-analysis-cellcog)\n\n## Skill Output:\n\n**Output Type(s):** [text, markdown, code, shell commands, configuration, guidance]\n\n**Output Format:** [Markdown guidance with Python snippets and requested financial deliverables such as HTML dashboards, PDF reports, XLSX spreadsheets, or Markdown analysis.]\n\n**Output Parameters:** [1D]\n\n**Other Properties Related to Output:** [Requires python3 and CELLCOG_API_KEY; may use the CellCog dependency and external CellCog service.]\n\n## Skill Version(s):\n\n1.0.17 (source: server release metadata)\n\n## Ethical Considerations:\n\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.\n\nArchive v1.0.16: 3 files, 5905 bytes\n\nFiles: skill-card.md (2243b), SKILL.md (9384b), _meta.json (142b)\n\nFile v1.0.16:SKILL.md\n\n---\nname: stock-analysis-cellcog\ndescription: \"AI financial analysis and stock research powered by CellCog. Stock analysis, valuation models, portfolio optimization, earnings breakdowns, investment research, financial statements, tax planning, DCF modeling. Deliverables as interactive dashboards, PDF reports, and Excel models.\"\nmetadata:\n  openclaw:\n    emoji: \"💰\"\n    os: [darwin, linux, windows]\n    requires:\n      bins: [python3]\n      env: [CELLCOG_API_KEY]\nauthor: CellCog\nhomepage: https://cellcog.ai\ndependencies: [cellcog]\n---\n# Stock Analysis - Wall Street-Grade Analysis, Accessible Globally\n\n**Wall Street-grade analysis, accessible globally.** Deep financial reasoning powered by #1 on DeepResearch Bench (Apr 2026) + SOTA financial models.\n\nThe best financial analysis has always lived behind Bloomberg terminals, institutional research desks, and $500/hour consultants. CellCog brings that same depth — stock analysis, valuation models, portfolio optimization, earnings breakdowns — to anyone with a prompt. From raw tickers to boardroom-ready deliverables in one request.\n\n## How to Use\n\nFor your first CellCog task in a session, read the **cellcog** skill for the full SDK reference — file handling, chat modes, timeouts, and more.\n\n**OpenClaw (fire-and-forget):**\n```python\nresult = client.create_chat(\n    prompt=\"[your task prompt]\",\n    notify_session_key=\"agent:main:main\",\n    task_label=\"my-task\",\n    chat_mode=\"team\",\n)\n```\n\n**All agents except OpenClaw (blocks until done):**\n```python\nfrom cellcog import CellCogClient\nclient = CellCogClient(agent_provider=\"openclaw|cursor|claude-code|codex|...\")\nresult = client.create_chat(\n    prompt=\"[your task prompt]\",\n    task_label=\"my-task\",\n    chat_mode=\"team\",\n)\nprint(result[\"message\"])\n```\n\n\n---\n\n## What Financial Work You Can Do\n\n### Stock & Equity Analysis\n\nDeep dives into public companies:\n\n- **Company Analysis**: \"Analyze NVIDIA — revenue trends, margins, competitive moat, and forward guidance\"\n- **Earnings Breakdowns**: \"Break down Apple's Q4 2025 earnings — beat/miss, segment performance, management commentary\"\n- **Valuation Models**: \"Build a DCF model for Microsoft with bear, base, and bull scenarios\"\n- **Peer Comparisons**: \"Compare semiconductor stocks — NVDA, AMD, INTC, TSM — on valuation, growth, and profitability metrics\"\n- **Technical Analysis**: \"Analyze Tesla's price action — key support/resistance levels, moving averages, and volume trends\"\n\n**Example prompt:**\n> \"Create a comprehensive stock analysis for Palantir (PLTR):\n> \n> Cover:\n> - Business model and revenue breakdown (government vs commercial)\n> - Last 4 quarters earnings performance\n> - Key financial metrics (P/E, P/S, FCF margin, revenue growth)\n> - Competitive positioning vs Snowflake, Databricks, C3.ai\n> - Bull and bear thesis\n> - Valuation assessment\n> \n> Deliver as an interactive HTML report with charts.\"\n\n### Portfolio Analysis & Optimization\n\nManage and optimize investments:\n\n- **Portfolio Review**: \"Analyze my portfolio: 40% AAPL, 20% MSFT, 15% GOOGL, 15% AMZN, 10% TSLA — diversification, risk, and recommendations\"\n- **Asset Allocation**: \"Design an optimal portfolio for a 35-year-old with $200K, moderate risk tolerance\"\n- **Risk Assessment**: \"Calculate the Sharpe ratio, beta, and maximum drawdown for this portfolio over the last 3 years\"\n- **Rebalancing**: \"My portfolio drifted from target — recommend rebalancing trades to minimize tax impact\"\n\n### Financial Modeling\n\nBuild professional financial models:\n\n- **DCF Models**: \"Build a discounted cash flow model for Shopify with sensitivity analysis on growth and discount rate\"\n- **Startup Financial Models**: \"Create a 3-year financial projection for a B2B SaaS with $50K MRR growing 15% monthly\"\n- **LBO Models**: \"Model a leveraged buyout scenario for a $100M revenue company at 8x EBITDA\"\n- **Scenario Analysis**: \"Create a 3-scenario model (recession, baseline, boom) for a retail REIT portfolio\"\n\n### Financial Documents & Reports\n\nProfessional financial deliverables:\n\n- **Investment Memos**: \"Write an investment memo recommending a position in CrowdStrike\"\n- **Quarterly Reports**: \"Create a quarterly financial report for my small business\"\n- **Financial Statements**: \"Generate pro forma financial statements for a startup fundraise\"\n- **Tax Planning**: \"Analyze tax optimization strategies for a freelancer earning $150K with $30K in capital gains\"\n\n### Personal Finance\n\nEveryday financial planning:\n\n- **Retirement Planning**: \"How much do I need to save monthly to retire at 55 with $2M? I'm 30, saving $2K/month currently\"\n- **Mortgage Analysis**: \"Compare a 15-year vs 30-year mortgage on a $500K home with 20% down at current rates\"\n- **Debt Payoff**: \"Create a debt payoff plan: $15K student loans at 5%, $8K credit card at 22%, $25K car loan at 6%\"\n- **Budget Optimization**: \"Analyze my spending breakdown and recommend where to cut to save $1,000/month more\"\n\n---\n\n## Output Formats\n\nCellCog delivers financial analysis in multiple formats:\n\n| Format | Best For |\n|--------|----------|\n| **Interactive HTML Dashboard** | Explorable charts, drill-down analysis, live data presentation |\n| **PDF Report** | Shareable, printable investment memos and reports |\n| **XLSX Spreadsheet** | Editable financial models, projections, calculations |\n| **Markdown** | Quick analysis for integration into your docs |\n\nSpecify your preferred format in the prompt:\n- \"Deliver as an interactive HTML report with charts\"\n- \"Create a PDF investment memo\"\n- \"Build this as an editable Excel model\"\n\n---\n\n## Choosing Mode & Tier\n\n**Use `chat_mode=\"team\"` — this is exactly what Agent Team exists for.** Deep research is THE Team use case: multi-source synthesis, cross-validation, citation verification, multiple reasoning passes.\n\n| Scenario | Recommended |\n|----------|-------------|\n| Deep financial analysis, valuation models, multi-company comparisons | `chat_mode=\"team\"` (default tier `\"core\"`) |\n| M&A due diligence, high-stakes investment decisions | `chat_mode=\"team\", chat_tier=\"max\"` (requires >=2,000 credits) |\n| Quick lookups, simple summaries | `chat_mode=\"agent\"` |\n\nLegacy names `\"agent team\"` / `\"agent team max\"` still work forever (they map to team core / team max).\n\n---\n\n## Example Prompts\n\n**Comprehensive stock analysis:**\n> \"Create a full investment analysis for AMD:\n> \n> 1. Business Overview — segments, revenue mix, competitive positioning\n> 2. Financial Performance — last 8 quarters revenue, margins, EPS trends\n> 3. Valuation — P/E, P/S, PEG vs peers (NVDA, INTC, QCOM)\n> 4. Growth Catalysts — AI/datacenter, gaming, embedded\n> 5. Risk Factors — competition, cyclicality, customer concentration\n> 6. Bull/Bear/Base price targets\n> \n> Interactive HTML report with comparison charts.\"\n\n**Financial model:**\n> \"Build a startup financial model:\n> \n> Business: B2B SaaS, project management tool\n> Current: $30K MRR, 200 customers, $150 ARPU\n> Growth: 12% MoM for 12 months, then 8% for next 12\n> Team: 8 people now, hiring 4 in next year\n> Expenses: $180K/month burn rate\n> \n> Create a 24-month projection showing:\n> - Revenue forecast with cohort analysis\n> - Expense breakdown and hiring plan\n> - Cash flow and runway\n> - Unit economics (CAC, LTV, payback period)\n> - Break-even analysis\n> \n> Deliver as Excel spreadsheet with charts.\"\n\n**Personal finance:**\n> \"I'm 28, earning $120K/year in San Francisco. I want to:\n> 1. Max out 401K contributions\n> 2. Build a 6-month emergency fund ($30K)\n> 3. Save for a house down payment ($100K in 5 years)\n> 4. Start investing in index funds\n> \n> Create a detailed monthly financial plan that shows how to prioritize these goals with my take-home pay after taxes. Include a timeline and visual roadmap.\"\n\n**Earnings analysis:**\n> \"Break down Tesla's most recent quarterly earnings:\n> \n> - Revenue vs estimates (beat/miss by how much?)\n> - Automotive margins — trend over last 4 quarters\n> - Energy and services segment performance\n> - Key quotes from management on guidance\n> - What analysts are saying post-earnings\n> - Bull and bear reactions\n> \n> Deliver as a concise PDF report with charts.\"\n\n---\n\n## Tips for Better Financial Analysis\n\n1. **Be specific about metrics**: \"Revenue growth\" is vague. \"YoY revenue growth for the last 8 quarters with segment breakdown\" is precise.\n\n2. **Specify time horizons**: \"Analyze AAPL\" is open-ended. \"Analyze AAPL's performance and outlook for the next 12 months\" is actionable.\n\n3. **State your purpose**: \"For an investment decision\", \"For a board presentation\", \"For personal planning\" — context shapes the analysis.\n\n4. **Include constraints**: Budget, risk tolerance, time horizon, tax situation — these matter for financial recommendations.\n\n5. **Request scenarios**: \"Include bear, base, and bull cases\" gives you a range, not just a point estimate.\n\n6. **Ask for the deliverable you need**: \"Interactive dashboard\", \"PDF memo\", \"Excel model\" — specify the format for the best result.\n\n---\n\n## If CellCog is not installed\n\n**Claude Code, Cursor, Codex + 70 more agents:** `npx skills add cellcog/skills --skill cellcog`\n**OpenClaw:** `clawhub install cellcog`\n**CellCog plugin users:** run `/cellcog-setup` (or `/cellcog:cellcog-setup` depending on your tool)\n**Manual setup:** `pip install -U cellcog` and set `CELLCOG_API_KEY`. See the **cellcog** skill for SDK reference.\n\nFile v1.0.16:_meta.json\n\n{\n  \"ownerId\": \"kn7a96cj9q65e0bhmzahv790en80ffqm\",\n  \"slug\": \"stock-analysis-cellcog\",\n  \"version\": \"1.0.16\",\n  \"publishedAt\": 1787535934970\n}\n\nFile v1.0.16:skill-card.md\n\n## Description:\n\nStock Analysis helps agents request CellCog-powered financial research, stock analysis, valuation models, portfolio optimization, earnings breakdowns, investment research, financial statements, tax planning, and DCF modeling.\n\nThis skill is ready for commercial/non-commercial use.\n\n## Publisher:\n\n[cellcog](https://clawhub.ai/user/cellcog)\n\n### License/Terms of Use:\n\nMIT-0\n\n## Use Case:\n\nExternal users, developers, and finance teams use this skill to request CellCog-powered stock research, valuation models, portfolio analysis, earnings breakdowns, personal finance planning, and financial deliverables.\n\n### Deployment Geography for Use:\n\nGlobal\n\n## Known Risks and Mitigations:\n\nRisk: The skill asks for sensitive personal or business financial details without a clear privacy or data-sharing notice for the CellCog API.\n\nMitigation: Review CellCog's privacy, retention, and logging policies before use; prefer redacted or aggregated inputs unless exact account-level details are necessary.\n\nRisk: Financial analysis, tax planning, portfolio optimization, and high-stakes investment outputs may affect real financial decisions.\n\nMitigation: Treat outputs as decision support, verify source data independently, and require qualified human review before trading, tax, or investment actions.\n\n## Reference(s):\n\n- [CellCog Homepage](https://cellcog.ai)\n- [ClawHub Skill Page](https://clawhub.ai/cellcog/skills/stock-analysis-cellcog)\n\n## Skill Output:\n\n**Output Type(s):** [Text, Markdown, Code, Shell commands, Configuration, Guidance, Files]\n\n**Output Format:** [Markdown guidance with Python examples; requested deliverables may include interactive HTML dashboards, PDF reports, XLSX spreadsheets, and Markdown.]\n\n**Output Parameters:** [1D]\n\n**Other Properties Related to Output:** [Requires python3 and CELLCOG_API_KEY; supports darwin, linux, and windows according to ClawHub metadata.]\n\n## Skill Version(s):\n\n1.0.16 (source: server release metadata)\n\n## Ethical Considerations:\n\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.\n\nArchive v1.0.15: 3 files, 5946 bytes\n\nFiles: skill-card.md (2306b), SKILL.md (9677b), _meta.json (142b)\n\nFile v1.0.15:SKILL.md\n\n---\nname: stock-analysis-cellcog\ndescription: \"AI financial analysis and stock research powered by CellCog. Stock analysis, valuation models, portfolio optimization, earnings breakdowns, investment research, financial statements, tax planning, DCF modeling. Deliverables as interactive dashboards, PDF reports, and Excel models.\"\nmetadata:\n  openclaw:\n    emoji: \"💰\"\n    os: [darwin, linux, windows]\n    requires:\n      bins: [python3]\n      env: [CELLCOG_API_KEY]\nauthor: CellCog\nhomepage: https://cellcog.ai\ndependencies: [cellcog]\n---\n# Stock Analysis - Wall Street-Grade Analysis, Accessible Globally\n\n**Wall Street-grade analysis, accessible globally.** Deep financial reasoning powered by #1 on DeepResearch Bench (Apr 2026) + SOTA financial models.\n\nThe best financial analysis has always lived behind Bloomberg terminals, institutional research desks, and $500/hour consultants. CellCog brings that same depth — stock analysis, valuation models, portfolio optimization, earnings breakdowns — to anyone with a prompt. From raw tickers to boardroom-ready deliverables in one request.\n\n## How to Use\n\nFor your first CellCog task in a session, read the **cellcog** skill for the full SDK reference — file handling, chat modes, timeouts, and more.\n\n**OpenClaw (fire-and-forget):**\n```python\nresult = client.create_chat(\n    prompt=\"[your task prompt]\",\n    notify_session_key=\"agent:main:main\",\n    task_label=\"my-task\",\n    chat_mode=\"agent\",\n)\n```\n\n**All agents except OpenClaw (blocks until done):**\n```python\nfrom cellcog import CellCogClient\nclient = CellCogClient(agent_provider=\"openclaw|cursor|claude-code|codex|...\")\nresult = client.create_chat(\n    prompt=\"[your task prompt]\",\n    task_label=\"my-task\",\n    chat_mode=\"agent\",\n)\nprint(result[\"message\"])\n```\n\n\n---\n\n## What Financial Work You Can Do\n\n### Stock & Equity Analysis\n\nDeep dives into public companies:\n\n- **Company Analysis**: \"Analyze NVIDIA — revenue trends, margins, competitive moat, and forward guidance\"\n- **Earnings Breakdowns**: \"Break down Apple's Q4 2025 earnings — beat/miss, segment performance, management commentary\"\n- **Valuation Models**: \"Build a DCF model for Microsoft with bear, base, and bull scenarios\"\n- **Peer Comparisons**: \"Compare semiconductor stocks — NVDA, AMD, INTC, TSM — on valuation, growth, and profitability metrics\"\n- **Technical Analysis**: \"Analyze Tesla's price action — key support/resistance levels, moving averages, and volume trends\"\n\n**Example prompt:**\n> \"Create a comprehensive stock analysis for Palantir (PLTR):\n> \n> Cover:\n> - Business model and revenue breakdown (government vs commercial)\n> - Last 4 quarters earnings performance\n> - Key financial metrics (P/E, P/S, FCF margin, revenue growth)\n> - Competitive positioning vs Snowflake, Databricks, C3.ai\n> - Bull and bear thesis\n> - Valuation assessment\n> \n> Deliver as an interactive HTML report with charts.\"\n\n### Portfolio Analysis & Optimization\n\nManage and optimize investments:\n\n- **Portfolio Review**: \"Analyze my portfolio: 40% AAPL, 20% MSFT, 15% GOOGL, 15% AMZN, 10% TSLA — diversification, risk, and recommendations\"\n- **Asset Allocation**: \"Design an optimal portfolio for a 35-year-old with $200K, moderate risk tolerance\"\n- **Risk Assessment**: \"Calculate the Sharpe ratio, beta, and maximum drawdown for this portfolio over the last 3 years\"\n- **Rebalancing**: \"My portfolio drifted from target — recommend rebalancing trades to minimize tax impact\"\n\n### Financial Modeling\n\nBuild professional financial models:\n\n- **DCF Models**: \"Build a discounted cash flow model for Shopify with sensitivity analysis on growth and discount rate\"\n- **Startup Financial Models**: \"Create a 3-year financial projection for a B2B SaaS with $50K MRR growing 15% monthly\"\n- **LBO Models**: \"Model a leveraged buyout scenario for a $100M revenue company at 8x EBITDA\"\n- **Scenario Analysis**: \"Create a 3-scenario model (recession, baseline, boom) for a retail REIT portfolio\"\n\n### Financial Documents & Reports\n\nProfessional financial deliverables:\n\n- **Investment Memos**: \"Write an investment memo recommending a position in CrowdStrike\"\n- **Quarterly Reports**: \"Create a quarterly financial report for my small business\"\n- **Financial Statements**: \"Generate pro forma financial statements for a startup fundraise\"\n- **Tax Planning**: \"Analyze tax optimization strategies for a freelancer earning $150K with $30K in capital gains\"\n\n### Personal Finance\n\nEveryday financial planning:\n\n- **Retirement Planning**: \"How much do I need to save monthly to retire at 55 with $2M? I'm 30, saving $2K/month currently\"\n- **Mortgage Analysis**: \"Compare a 15-year vs 30-year mortgage on a $500K home with 20% down at current rates\"\n- **Debt Payoff**: \"Create a debt payoff plan: $15K student loans at 5%, $8K credit card at 22%, $25K car loan at 6%\"\n- **Budget Optimization**: \"Analyze my spending breakdown and recommend where to cut to save $1,000/month more\"\n\n---\n\n## Output Formats\n\nCellCog delivers financial analysis in multiple formats:\n\n| Format | Best For |\n|--------|----------|\n| **Interactive HTML Dashboard** | Explorable charts, drill-down analysis, live data presentation |\n| **PDF Report** | Shareable, printable investment memos and reports |\n| **XLSX Spreadsheet** | Editable financial models, projections, calculations |\n| **Markdown** | Quick analysis for integration into your docs |\n\nSpecify your preferred format in the prompt:\n- \"Deliver as an interactive HTML report with charts\"\n- \"Create a PDF investment memo\"\n- \"Build this as an editable Excel model\"\n\n---\n\n## Chat Mode for Finance\n\n| Scenario | Recommended Mode |\n|----------|------------------|\n| Quick lookups, single stock metrics, basic calculations | `\"agent\"` |\n| Deep analysis, valuation models, multi-company comparisons, investment research | `\"agent team\"` |\n| High-stakes investment decisions, M&A due diligence, institutional-grade research | `\"agent team max\"` |\n\n**Use `\"agent team\"` for most financial analysis.** Financial work demands deep reasoning, data cross-referencing, and multi-source synthesis. Agent team mode delivers the depth that serious financial analysis requires.\n\n**Use `\"agent\"` for quick financial lookups** — current stock price, simple calculations, or basic metric checks.\n\n**Use `\"agent team max\"` for high-stakes financial work** — investment decisions with significant capital at risk, M&A due diligence, regulatory filings, or boardroom-ready deliverables where the extra reasoning depth justifies the cost. Requires ≥2,000 credits.\n\n---\n\n## Example Prompts\n\n**Comprehensive stock analysis:**\n> \"Create a full investment analysis for AMD:\n> \n> 1. Business Overview — segments, revenue mix, competitive positioning\n> 2. Financial Performance — last 8 quarters revenue, margins, EPS trends\n> 3. Valuation — P/E, P/S, PEG vs peers (NVDA, INTC, QCOM)\n> 4. Growth Catalysts — AI/datacenter, gaming, embedded\n> 5. Risk Factors — competition, cyclicality, customer concentration\n> 6. Bull/Bear/Base price targets\n> \n> Interactive HTML report with comparison charts.\"\n\n**Financial model:**\n> \"Build a startup financial model:\n> \n> Business: B2B SaaS, project management tool\n> Current: $30K MRR, 200 customers, $150 ARPU\n> Growth: 12% MoM for 12 months, then 8% for next 12\n> Team: 8 people now, hiring 4 in next year\n> Expenses: $180K/month burn rate\n> \n> Create a 24-month projection showing:\n> - Revenue forecast with cohort analysis\n> - Expense breakdown and hiring plan\n> - Cash flow and runway\n> - Unit economics (CAC, LTV, payback period)\n> - Break-even analysis\n> \n> Deliver as Excel spreadsheet with charts.\"\n\n**Personal finance:**\n> \"I'm 28, earning $120K/year in San Francisco. I want to:\n> 1. Max out 401K contributions\n> 2. Build a 6-month emergency fund ($30K)\n> 3. Save for a house down payment ($100K in 5 years)\n> 4. Start investing in index funds\n> \n> Create a detailed monthly financial plan that shows how to prioritize these goals with my take-home pay after taxes. Include a timeline and visual roadmap.\"\n\n**Earnings analysis:**\n> \"Break down Tesla's most recent quarterly earnings:\n> \n> - Revenue vs estimates (beat/miss by how much?)\n> - Automotive margins — trend over last 4 quarters\n> - Energy and services segment performance\n> - Key quotes from management on guidance\n> - What analysts are saying post-earnings\n> - Bull and bear reactions\n> \n> Deliver as a concise PDF report with charts.\"\n\n---\n\n## Tips for Better Financial Analysis\n\n1. **Be specific about metrics**: \"Revenue growth\" is vague. \"YoY revenue growth for the last 8 quarters with segment breakdown\" is precise.\n\n2. **Specify time horizons**: \"Analyze AAPL\" is open-ended. \"Analyze AAPL's performance and outlook for the next 12 months\" is actionable.\n\n3. **State your purpose**: \"For an investment decision\", \"For a board presentation\", \"For personal planning\" — context shapes the analysis.\n\n4. **Include constraints**: Budget, risk tolerance, time horizon, tax situation — these matter for financial recommendations.\n\n5. **Request scenarios**: \"Include bear, base, and bull cases\" gives you a range, not just a point estimate.\n\n6. **Ask for the deliverable you need**: \"Interactive dashboard\", \"PDF memo\", \"Excel model\" — specify the format for the best result.\n\n---\n\n## If CellCog is not installed\n\n**Claude Code, Cursor, Codex + 70 more agents:** `npx skills add cellcog/skills --skill cellcog`\n**OpenClaw:** `clawhub install cellcog`\n**CellCog plugin users:** run `/cellcog-setup` (or `/cellcog:cellcog-setup` depending on your tool)\n**Manual setup:** `pip install -U cellcog` and set `CELLCOG_API_KEY`. See the **cellcog** skill for SDK reference.\n\nFile v1.0.15:_meta.json\n\n{\n  \"ownerId\": \"kn7a96cj9q65e0bhmzahv790en80ffqm\",\n  \"slug\": \"stock-analysis-cellcog\",\n  \"version\": \"1.0.15\",\n  \"publishedAt\": 1785737158296\n}\n\nFile v1.0.15:skill-card.md\n\n## Description: <br>\nAI financial analysis and stock research powered by CellCog, including stock analysis, valuation models, portfolio optimization, earnings breakdowns, investment research, financial statements, tax planning, and DCF modeling with deliverables as interactive dashboards, PDF reports, and Excel models. <br>\n\nThis skill is ready for commercial/non-commercial use. <br>\n\n## Publisher: <br>\n[cellcog](https://clawhub.ai/user/cellcog) <br>\n\n### License/Terms of Use: <br>\nMIT-0 <br>\n\n\n## Use Case: <br>\nDevelopers, agents, and external users use this skill to route financial research and modeling tasks to CellCog, including equity analysis, portfolio review, valuation models, investment memos, personal finance planning, and report generation. <br>\n\n### Deployment Geography for Use: <br>\nGlobal <br>\n\n## Known Risks and Mitigations: <br>\nRisk: Financial, tax, and investment outputs may be incorrect, incomplete, or unsuitable as professional advice. <br>\nMitigation: Treat outputs as informational, verify market data and assumptions, and consult qualified financial, tax, investment, or legal professionals before acting on recommendations. <br>\nRisk: Prompts and uploaded financial details may be processed by CellCog. <br>\nMitigation: Avoid sharing unnecessary sensitive data and provide only the information needed for the requested analysis. <br>\n\n\n## Reference(s): <br>\n- [CellCog homepage](https://cellcog.ai) <br>\n- [Stock Analysis on ClawHub](https://clawhub.ai/cellcog/skills/stock-analysis-cellcog) <br>\n\n\n## Skill Output: <br>\n**Output Type(s):** [Text, Markdown, Code, Shell commands, Configuration, Guidance, Files] <br>\n**Output Format:** [Markdown with Python snippets and optional HTML, PDF, or XLSX deliverables] <br>\n**Output Parameters:** [1D] <br>\n**Other Properties Related to Output:** [Requires python3, the CellCog SDK, and CELLCOG_API_KEY; deeper finance workflows may require additional CellCog credits.] <br>\n\n## Skill Version(s): <br>\n1.0.15 (source: server release metadata) <br>\n\n## Ethical Considerations: <br>\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment. <br>\n\nArchive v1.0.14: 3 files, 5953 bytes\n\nFiles: skill-card.md (2498b), SKILL.md (9602b), _meta.json (142b)\n\nFile v1.0.14:SKILL.md\n\n---\nname: stock-analysis-cellcog\ndescription: \"AI financial analysis and stock research powered by CellCog. Stock analysis, valuation models, portfolio optimization, earnings breakdowns, investment research, financial statements, tax planning, DCF modeling. Deliverables as interactive dashboards, PDF reports, and Excel models.\"\nmetadata:\n  openclaw:\n    emoji: \"💰\"\n    os: [darwin, linux, windows]\n    requires:\n      bins: [python3]\n      env: [CELLCOG_API_KEY]\nauthor: CellCog\nhomepage: https://cellcog.ai\ndependencies: [cellcog]\n---\n# Stock Analysis - Wall Street-Grade Analysis, Accessible Globally\n\n**Wall Street-grade analysis, accessible globally.** Deep financial reasoning powered by #1 on DeepResearch Bench (Apr 2026) + SOTA financial models.\n\nThe best financial analysis has always lived behind Bloomberg terminals, institutional research desks, and $500/hour consultants. CellCog brings that same depth — stock analysis, valuation models, portfolio optimization, earnings breakdowns — to anyone with a prompt. From raw tickers to boardroom-ready deliverables in one request.\n\n## How to Use\n\nFor your first CellCog task in a session, read the **cellcog** skill for the full SDK reference — file handling, chat modes, timeouts, and more.\n\n**OpenClaw (fire-and-forget):**\n```python\nresult = client.create_chat(\n    prompt=\"[your task prompt]\",\n    notify_session_key=\"agent:main:main\",\n    task_label=\"my-task\",\n    chat_mode=\"agent\",\n)\n```\n\n**All agents except OpenClaw (blocks until done):**\n```python\nfrom cellcog import CellCogClient\nclient = CellCogClient(agent_provider=\"openclaw|cursor|claude-code|codex|...\")\nresult = client.create_chat(\n    prompt=\"[your task prompt]\",\n    task_label=\"my-task\",\n    chat_mode=\"agent\",\n)\nprint(result[\"message\"])\n```\n\n\n---\n\n## What Financial Work You Can Do\n\n### Stock & Equity Analysis\n\nDeep dives into public companies:\n\n- **Company Analysis**: \"Analyze NVIDIA — revenue trends, margins, competitive moat, and forward guidance\"\n- **Earnings Breakdowns**: \"Break down Apple's Q4 2025 earnings — beat/miss, segment performance, management commentary\"\n- **Valuation Models**: \"Build a DCF model for Microsoft with bear, base, and bull scenarios\"\n- **Peer Comparisons**: \"Compare semiconductor stocks — NVDA, AMD, INTC, TSM — on valuation, growth, and profitability metrics\"\n- **Technical Analysis**: \"Analyze Tesla's price action — key support/resistance levels, moving averages, and volume trends\"\n\n**Example prompt:**\n> \"Create a comprehensive stock analysis for Palantir (PLTR):\n> \n> Cover:\n> - Business model and revenue breakdown (government vs commercial)\n> - Last 4 quarters earnings performance\n> - Key financial metrics (P/E, P/S, FCF margin, revenue growth)\n> - Competitive positioning vs Snowflake, Databricks, C3.ai\n> - Bull and bear thesis\n> - Valuation assessment\n> \n> Deliver as an interactive HTML report with charts.\"\n\n### Portfolio Analysis & Optimization\n\nManage and optimize investments:\n\n- **Portfolio Review**: \"Analyze my portfolio: 40% AAPL, 20% MSFT, 15% GOOGL, 15% AMZN, 10% TSLA — diversification, risk, and recommendations\"\n- **Asset Allocation**: \"Design an optimal portfolio for a 35-year-old with $200K, moderate risk tolerance\"\n- **Risk Assessment**: \"Calculate the Sharpe ratio, beta, and maximum drawdown for this portfolio over the last 3 years\"\n- **Rebalancing**: \"My portfolio drifted from target — recommend rebalancing trades to minimize tax impact\"\n\n### Financial Modeling\n\nBuild professional financial models:\n\n- **DCF Models**: \"Build a discounted cash flow model for Shopify with sensitivity analysis on growth and discount rate\"\n- **Startup Financial Models**: \"Create a 3-year financial projection for a B2B SaaS with $50K MRR growing 15% monthly\"\n- **LBO Models**: \"Model a leveraged buyout scenario for a $100M revenue company at 8x EBITDA\"\n- **Scenario Analysis**: \"Create a 3-scenario model (recession, baseline, boom) for a retail REIT portfolio\"\n\n### Financial Documents & Reports\n\nProfessional financial deliverables:\n\n- **Investment Memos**: \"Write an investment memo recommending a position in CrowdStrike\"\n- **Quarterly Reports**: \"Create a quarterly financial report for my small business\"\n- **Financial Statements**: \"Generate pro forma financial statements for a startup fundraise\"\n- **Tax Planning**: \"Analyze tax optimization strategies for a freelancer earning $150K with $30K in capital gains\"\n\n### Personal Finance\n\nEveryday financial planning:\n\n- **Retirement Planning**: \"How much do I need to save monthly to retire at 55 with $2M? I'm 30, saving $2K/month currently\"\n- **Mortgage Analysis**: \"Compare a 15-year vs 30-year mortgage on a $500K home with 20% down at current rates\"\n- **Debt Payoff**: \"Create a debt payoff plan: $15K student loans at 5%, $8K credit card at 22%, $25K car loan at 6%\"\n- **Budget Optimization**: \"Analyze my spending breakdown and recommend where to cut to save $1,000/month more\"\n\n---\n\n## Output Formats\n\nCellCog delivers financial analysis in multiple formats:\n\n| Format | Best For |\n|--------|----------|\n| **Interactive HTML Dashboard** | Explorable charts, drill-down analysis, live data presentation |\n| **PDF Report** | Shareable, printable investment memos and reports |\n| **XLSX Spreadsheet** | Editable financial models, projections, calculations |\n| **Markdown** | Quick analysis for integration into your docs |\n\nSpecify your preferred format in the prompt:\n- \"Deliver as an interactive HTML report with charts\"\n- \"Create a PDF investment memo\"\n- \"Build this as an editable Excel model\"\n\n---\n\n## Chat Mode for Finance\n\n| Scenario | Recommended Mode |\n|----------|------------------|\n| Quick lookups, single stock metrics, basic calculations | `\"agent\"` |\n| Deep analysis, valuation models, multi-company comparisons, investment research | `\"agent team\"` |\n| High-stakes investment decisions, M&A due diligence, institutional-grade research | `\"agent team max\"` |\n\n**Use `\"agent team\"` for most financial analysis.** Financial work demands deep reasoning, data cross-referencing, and multi-source synthesis. Agent team mode delivers the depth that serious financial analysis requires.\n\n**Use `\"agent\"` for quick financial lookups** — current stock price, simple calculations, or basic metric checks.\n\n**Use `\"agent team max\"` for high-stakes financial work** — investment decisions with significant capital at risk, M&A due diligence, regulatory filings, or boardroom-ready deliverables where the extra reasoning depth justifies the cost. Requires ≥2,000 credits.\n\n---\n\n## Example Prompts\n\n**Comprehensive stock analysis:**\n> \"Create a full investment analysis for AMD:\n> \n> 1. Business Overview — segments, revenue mix, competitive positioning\n> 2. Financial Performance — last 8 quarters revenue, margins, EPS trends\n> 3. Valuation — P/E, P/S, PEG vs peers (NVDA, INTC, QCOM)\n> 4. Growth Catalysts — AI/datacenter, gaming, embedded\n> 5. Risk Factors — competition, cyclicality, customer concentration\n> 6. Bull/Bear/Base price targets\n> \n> Interactive HTML report with comparison charts.\"\n\n**Financial model:**\n> \"Build a startup financial model:\n> \n> Business: B2B SaaS, project management tool\n> Current: $30K MRR, 200 customers, $150 ARPU\n> Growth: 12% MoM for 12 months, then 8% for next 12\n> Team: 8 people now, hiring 4 in next year\n> Expenses: $180K/month burn rate\n> \n> Create a 24-month projection showing:\n> - Revenue forecast with cohort analysis\n> - Expense breakdown and hiring plan\n> - Cash flow and runway\n> - Unit economics (CAC, LTV, payback period)\n> - Break-even analysis\n> \n> Deliver as Excel spreadsheet with charts.\"\n\n**Personal finance:**\n> \"I'm 28, earning $120K/year in San Francisco. I want to:\n> 1. Max out 401K contributions\n> 2. Build a 6-month emergency fund ($30K)\n> 3. Save for a house down payment ($100K in 5 years)\n> 4. Start investing in index funds\n> \n> Create a detailed monthly financial plan that shows how to prioritize these goals with my take-home pay after taxes. Include a timeline and visual roadmap.\"\n\n**Earnings analysis:**\n> \"Break down Tesla's most recent quarterly earnings:\n> \n> - Revenue vs estimates (beat/miss by how much?)\n> - Automotive margins — trend over last 4 quarters\n> - Energy and services segment performance\n> - Key quotes from management on guidance\n> - What analysts are saying post-earnings\n> - Bull and bear reactions\n> \n> Deliver as a concise PDF report with charts.\"\n\n---\n\n## Tips for Better Financial Analysis\n\n1. **Be specific about metrics**: \"Revenue growth\" is vague. \"YoY revenue growth for the last 8 quarters with segment breakdown\" is precise.\n\n2. **Specify time horizons**: \"Analyze AAPL\" is open-ended. \"Analyze AAPL's performance and outlook for the next 12 months\" is actionable.\n\n3. **State your purpose**: \"For an investment decision\", \"For a board presentation\", \"For personal planning\" — context shapes the analysis.\n\n4. **Include constraints**: Budget, risk tolerance, time horizon, tax situation — these matter for financial recommendations.\n\n5. **Request scenarios**: \"Include bear, base, and bull cases\" gives you a range, not just a point estimate.\n\n6. **Ask for the deliverable you need**: \"Interactive dashboard\", \"PDF memo\", \"Excel model\" — specify the format for the best result.\n\n---\n\n## If CellCog is not installed\n\nRun `/cellcog-setup` (or `/cellcog:cellcog-setup` depending on your tool) to install and authenticate.\n**OpenClaw users:** Run `clawhub install cellcog` instead.\n**Manual setup:** `pip install -U cellcog` and set `CELLCOG_API_KEY`. See the **cellcog** skill for SDK reference.\n\nFile v1.0.14:_meta.json\n\n{\n  \"ownerId\": \"kn7a96cj9q65e0bhmzahv790en80ffqm\",\n  \"slug\": \"stock-analysis-cellcog\",\n  \"version\": \"1.0.14\",\n  \"publishedAt\": 1785703605778\n}\n\nFile v1.0.14:skill-card.md\n\n## Description: <br>\nAI financial analysis and stock research powered by CellCog, covering stock analysis, valuation models, portfolio optimization, earnings breakdowns, investment research, financial statements, tax planning, and DCF modeling. <br>\n\nThis skill is ready for commercial/non-commercial use. <br>\n\n## Publisher: <br>\n[cellcog](https://clawhub.ai/user/cellcog) <br>\n\n### License/Terms of Use: <br>\nMIT-0 <br>\n\n\n## Use Case: <br>\nDevelopers, analysts, and finance users use this skill to ask CellCog for stock research, portfolio review, valuation modeling, financial documents, tax-planning analysis, and personal-finance planning. The skill supports prompts that request interactive dashboards, PDF reports, Excel models, or Markdown summaries. <br>\n\n### Deployment Geography for Use: <br>\nGlobal <br>\n\n## Known Risks and Mitigations: <br>\nRisk: Financial prompts may be sent to CellCog as an external financial-analysis service. <br>\nMitigation: Avoid submitting account numbers, tax IDs, unreleased business financials, client data, or other confidential details unless CellCog's data handling terms are understood and accepted. <br>\nRisk: Financial, investment, tax, or planning outputs may be used for high-stakes decisions. <br>\nMitigation: Review outputs with appropriate professional judgment before acting, especially for significant capital decisions, tax planning, regulatory filings, or boardroom-ready deliverables. <br>\n\n\n## Reference(s): <br>\n- [ClawHub Skill Page](https://clawhub.ai/cellcog/skills/stock-analysis-cellcog) <br>\n- [CellCog Homepage](https://cellcog.ai) <br>\n- [ClawHub Publisher Profile](https://clawhub.ai/user/cellcog) <br>\n\n\n## Skill Output: <br>\n**Output Type(s):** [Analysis, Markdown, Code, Configuration, Guidance, Files] <br>\n**Output Format:** [Markdown guidance with Python examples; requested deliverables may include interactive HTML dashboards, PDF reports, XLSX spreadsheets, or Markdown summaries.] <br>\n**Output Parameters:** [1D] <br>\n**Other Properties Related to Output:** [Requires python3, the cellcog dependency, and CELLCOG_API_KEY. Financial prompts may be sent to CellCog.] <br>\n\n## Skill Version(s): <br>\n1.0.14 (source: server release evidence) <br>\n\n## Ethical Considerations: <br>\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment. <br>\n\nArchive v1.0.13: 3 files, 5869 bytes\n\nFiles: skill-card.md (2264b), SKILL.md (9602b), _meta.json (142b)\n\nFile v1.0.13:SKILL.md\n\n---\nname: stock-analysis-cellcog\ndescription: \"AI financial analysis and stock research powered by CellCog. Stock analysis, valuation models, portfolio optimization, earnings breakdowns, investment research, financial statements, tax planning, DCF modeling. Deliverables as interactive dashboards, PDF reports, and Excel models.\"\nmetadata:\n  openclaw:\n    emoji: \"💰\"\n    os: [darwin, linux, windows]\n    requires:\n      bins: [python3]\n      env: [CELLCOG_API_KEY]\nauthor: CellCog\nhomepage: https://cellcog.ai\ndependencies: [cellcog]\n---\n# Stock Analysis - Wall Street-Grade Analysis, Accessible Globally\n\n**Wall Street-grade analysis, accessible globally.** Deep financial reasoning powered by #1 on DeepResearch Bench (Apr 2026) + SOTA financial models.\n\nThe best financial analysis has always lived behind Bloomberg terminals, institutional research desks, and $500/hour consultants. CellCog brings that same depth — stock analysis, valuation models, portfolio optimization, earnings breakdowns — to anyone with a prompt. From raw tickers to boardroom-ready deliverables in one request.\n\n## How to Use\n\nFor your first CellCog task in a session, read the **cellcog** skill for the full SDK reference — file handling, chat modes, timeouts, and more.\n\n**OpenClaw (fire-and-forget):**\n```python\nresult = client.create_chat(\n    prompt=\"[your task prompt]\",\n    notify_session_key=\"agent:main:main\",\n    task_label=\"my-task\",\n    chat_mode=\"agent\",\n)\n```\n\n**All agents except OpenClaw (blocks until done):**\n```python\nfrom cellcog import CellCogClient\nclient = CellCogClient(agent_provider=\"openclaw|cursor|claude-code|codex|...\")\nresult = client.create_chat(\n    prompt=\"[your task prompt]\",\n    task_label=\"my-task\",\n    chat_mode=\"agent\",\n)\nprint(result[\"message\"])\n```\n\n\n---\n\n## What Financial Work You Can Do\n\n### Stock & Equity Analysis\n\nDeep dives into public companies:\n\n- **Company Analysis**: \"Analyze NVIDIA — revenue trends, margins, competitive moat, and forward guidance\"\n- **Earnings Breakdowns**: \"Break down Apple's Q4 2025 earnings — beat/miss, segment performance, management commentary\"\n- **Valuation Models**: \"Build a DCF model for Microsoft with bear, base, and bull scenarios\"\n- **Peer Comparisons**: \"Compare semiconductor stocks — NVDA, AMD, INTC, TSM — on valuation, growth, and profitability metrics\"\n- **Technical Analysis**: \"Analyze Tesla's price action — key support/resistance levels, moving averages, and volume trends\"\n\n**Example prompt:**\n> \"Create a comprehensive stock analysis for Palantir (PLTR):\n> \n> Cover:\n> - Business model and revenue breakdown (government vs commercial)\n> - Last 4 quarters earnings performance\n> - Key financial metrics (P/E, P/S, FCF margin, revenue growth)\n> - Competitive positioning vs Snowflake, Databricks, C3.ai\n> - Bull and bear thesis\n> - Valuation assessment\n> \n> Deliver as an interactive HTML report with charts.\"\n\n### Portfolio Analysis & Optimization\n\nManage and optimize investments:\n\n- **Portfolio Review**: \"Analyze my portfolio: 40% AAPL, 20% MSFT, 15% GOOGL, 15% AMZN, 10% TSLA — diversification, risk, and recommendations\"\n- **Asset Allocation**: \"Design an optimal portfolio for a 35-year-old with $200K, moderate risk tolerance\"\n- **Risk Assessment**: \"Calculate the Sharpe ratio, beta, and maximum drawdown for this portfolio over the last 3 years\"\n- **Rebalancing**: \"My portfolio drifted from target — recommend rebalancing trades to minimize tax impact\"\n\n### Financial Modeling\n\nBuild professional financial models:\n\n- **DCF Models**: \"Build a discounted cash flow model for Shopify with sensitivity analysis on growth and discount rate\"\n- **Startup Financial Models**: \"Create a 3-year financial projection for a B2B SaaS with $50K MRR growing 15% monthly\"\n- **LBO Models**: \"Model a leveraged buyout scenario for a $100M revenue company at 8x EBITDA\"\n- **Scenario Analysis**: \"Create a 3-scenario model (recession, baseline, boom) for a retail REIT portfolio\"\n\n### Financial Documents & Reports\n\nProfessional financial deliverables:\n\n- **Investment Memos**: \"Write an investment memo recommending a position in CrowdStrike\"\n- **Quarterly Reports**: \"Create a quarterly financial report for my small business\"\n- **Financial Statements**: \"Generate pro forma financial statements for a startup fundraise\"\n- **Tax Planning**: \"Analyze tax optimization strategies for a freelancer earning $150K with $30K in capital gains\"\n\n### Personal Finance\n\nEveryday financial planning:\n\n- **Retirement Planning**: \"How much do I need to save monthly to retire at 55 with $2M? I'm 30, saving $2K/month currently\"\n- **Mortgage Analysis**: \"Compare a 15-year vs 30-year mortgage on a $500K home with 20% down at current rates\"\n- **Debt Payoff**: \"Create a debt payoff plan: $15K student loans at 5%, $8K credit card at 22%, $25K car loan at 6%\"\n- **Budget Optimization**: \"Analyze my spending breakdown and recommend where to cut to save $1,000/month more\"\n\n---\n\n## Output Formats\n\nCellCog delivers financial analysis in multiple formats:\n\n| Format | Best For |\n|--------|----------|\n| **Interactive HTML Dashboard** | Explorable charts, drill-down analysis, live data presentation |\n| **PDF Report** | Shareable, printable investment memos and reports |\n| **XLSX Spreadsheet** | Editable financial models, projections, calculations |\n| **Markdown** | Quick analysis for integration into your docs |\n\nSpecify your preferred format in the prompt:\n- \"Deliver as an interactive HTML report with charts\"\n- \"Create a PDF investment memo\"\n- \"Build this as an editable Excel model\"\n\n---\n\n## Chat Mode for Finance\n\n| Scenario | Recommended Mode |\n|----------|------------------|\n| Quick lookups, single stock metrics, basic calculations | `\"agent\"` |\n| Deep analysis, valuation models, multi-company comparisons, investment research | `\"agent team\"` |\n| High-stakes investment decisions, M&A due diligence, institutional-grade research | `\"agent team max\"` |\n\n**Use `\"agent team\"` for most financial analysis.** Financial work demands deep reasoning, data cross-referencing, and multi-source synthesis. Agent team mode delivers the depth that serious financial analysis requires.\n\n**Use `\"agent\"` for quick financial lookups** — current stock price, simple calculations, or basic metric checks.\n\n**Use `\"agent team max\"` for high-stakes financial work** — investment decisions with significant capital at risk, M&A due diligence, regulatory filings, or boardroom-ready deliverables where the extra reasoning depth justifies the cost. Requires ≥2,000 credits.\n\n---\n\n## Example Prompts\n\n**Comprehensive stock analysis:**\n> \"Create a full investment analysis for AMD:\n> \n> 1. Business Overview — segments, revenue mix, competitive positioning\n> 2. Financial Performance — last 8 quarters revenue, margins, EPS trends\n> 3. Valuation — P/E, P/S, PEG vs peers (NVDA, INTC, QCOM)\n> 4. Growth Catalysts — AI/datacenter, gaming, embedded\n> 5. Risk Factors — competition, cyclicality, customer concentration\n> 6. Bull/Bear/Base price targets\n> \n> Interactive HTML report with comparison charts.\"\n\n**Financial model:**\n> \"Build a startup financial model:\n> \n> Business: B2B SaaS, project management tool\n> Current: $30K MRR, 200 customers, $150 ARPU\n> Growth: 12% MoM for 12 months, then 8% for next 12\n> Team: 8 people now, hiring 4 in next year\n> Expenses: $180K/month burn rate\n> \n> Create a 24-month projection showing:\n> - Revenue forecast with cohort analysis\n> - Expense breakdown and hiring plan\n> - Cash flow and runway\n> - Unit economics (CAC, LTV, payback period)\n> - Break-even analysis\n> \n> Deliver as Excel spreadsheet with charts.\"\n\n**Personal finance:**\n> \"I'm 28, earning $120K/year in San Francisco. I want to:\n> 1. Max out 401K contributions\n> 2. Build a 6-month emergency fund ($30K)\n> 3. Save for a house down payment ($100K in 5 years)\n> 4. Start investing in index funds\n> \n> Create a detailed monthly financial plan that shows how to prioritize these goals with my take-home pay after taxes. Include a timeline and visual roadmap.\"\n\n**Earnings analysis:**\n> \"Break down Tesla's most recent quarterly earnings:\n> \n> - Revenue vs estimates (beat/miss by how much?)\n> - Automotive margins — trend over last 4 quarters\n> - Energy and services segment performance\n> - Key quotes from management on guidance\n> - What analysts are saying post-earnings\n> - Bull and bear reactions\n> \n> Deliver as a concise PDF report with charts.\"\n\n---\n\n## Tips for Better Financial Analysis\n\n1. **Be specific about metrics**: \"Revenue growth\" is vague. \"YoY revenue growth for the last 8 quarters with segment breakdown\" is precise.\n\n2. **Specify time horizons**: \"Analyze AAPL\" is open-ended. \"Analyze AAPL's performance and outlook for the next 12 months\" is actionable.\n\n3. **State your purpose**: \"For an investment decision\", \"For a board presentation\", \"For personal planning\" — context shapes the analysis.\n\n4. **Include constraints**: Budget, risk tolerance, time horizon, tax situation — these matter for financial recommendations.\n\n5. **Request scenarios**: \"Include bear, base, and bull cases\" gives you a range, not just a point estimate.\n\n6. **Ask for the deliverable you need**: \"Interactive dashboard\", \"PDF memo\", \"Excel model\" — specify the format for the best result.\n\n---\n\n## If CellCog is not installed\n\nRun `/cellcog-setup` (or `/cellcog:cellcog-setup` depending on your tool) to install and authenticate.\n**OpenClaw users:** Run `clawhub install cellcog` instead.\n**Manual setup:** `pip install -U cellcog` and set `CELLCOG_API_KEY`. See the **cellcog** skill for SDK reference.\n\nFile v1.0.13:_meta.json\n\n{\n  \"ownerId\": \"kn7a96cj9q65e0bhmzahv790en80ffqm\",\n  \"slug\": \"stock-analysis-cellcog\",\n  \"version\": \"1.0.13\",\n  \"publishedAt\": 1784259733283\n}\n\nFile v1.0.13:skill-card.md\n\n## Description: <br>\nStock Analysis Cellcog helps agents use CellCog for financial analysis and stock research, producing valuation models, portfolio analysis, earnings breakdowns, investment research, dashboards, PDF reports, and Excel models. <br>\n\nThis skill is ready for commercial/non-commercial use. <br>\n\n## Publisher: <br>\n[nitishgargiitd](https://clawhub.ai/user/nitishgargiitd) <br>\n\n### License/Terms of Use: <br>\nMIT-0 <br>\n\n\n## Use Case: <br>\nExternal users, developers, and analysts use this skill to route financial-analysis prompts through CellCog for stock research, portfolio review, financial modeling, personal finance planning, and report generation. <br>\n\n### Deployment Geography for Use: <br>\nGlobal <br>\n\n## Known Risks and Mitigations: <br>\nRisk: Sensitive financial prompts or uploaded context may be sent to CellCog. <br>\nMitigation: Do not include SSNs, account numbers, brokerage credentials, tax IDs, or other unnecessary identifiers. <br>\nRisk: CELLCOG_API_KEY could be exposed if placed in prompts or source files. <br>\nMitigation: Keep CELLCOG_API_KEY in an environment variable or secret manager. <br>\nRisk: Financial analysis can be incomplete, stale, or unsuitable for high-stakes decisions. <br>\nMitigation: Review outputs with appropriate financial, tax, or compliance expertise before acting on them. <br>\n\n\n## Reference(s): <br>\n- [CellCog homepage](https://cellcog.ai) <br>\n- [ClawHub skill page](https://clawhub.ai/nitishgargiitd/skills/stock-analysis-cellcog) <br>\n\n\n## Skill Output: <br>\n**Output Type(s):** [Text, Markdown, Code, Files, Configuration guidance] <br>\n**Output Format:** [Markdown guidance with Python examples; CellCog task outputs may be Markdown, interactive HTML, PDF, or XLSX.] <br>\n**Output Parameters:** [1D] <br>\n**Other Properties Related to Output:** [Requires python3 and CELLCOG_API_KEY; higher-depth CellCog modes may require credits.] <br>\n\n## Skill Version(s): <br>\n1.0.13 (source: ClawHub release metadata) <br>\n\n## Ethical Considerations: <br>\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment. <br>\n\nArchive v1.0.12: 3 files, 5852 bytes\n\nFiles: skill-card.md (2182b), SKILL.md (9580b), _meta.json (142b)\n\nFile v1.0.12:SKILL.md\n\n---\nname: fin-cog\ndescription: \"AI financial analysis and stock research powered by CellCog. Stock analysis, valuation models, portfolio optimization, earnings breakdowns, investment research, financial statements, tax planning, DCF modeling. Deliverables as interactive dashboards, PDF reports, and Excel models.\"\nmetadata:\n  openclaw:\n    emoji: \"💰\"\n    os: [darwin, linux, windows]\n    requires:\n      bins: [python3]\n      env: [CELLCOG_API_KEY]\nauthor: CellCog\nhomepage: https://cellcog.ai\ndependencies: [cellcog]\n---\n# Fin Cog - Wall Street-Grade Analysis, Accessible Globally\n\n**Wall Street-grade analysis, accessible globally.** Deep financial reasoning powered by #1 on DeepResearch Bench (Apr 2026) + SOTA financial models.\n\nThe best financial analysis has always lived behind Bloomberg terminals, institutional research desks, and $500/hour consultants. CellCog brings that same depth — stock analysis, valuation models, portfolio optimization, earnings breakdowns — to anyone with a prompt. From raw tickers to boardroom-ready deliverables in one request.\n\n## How to Use\n\nFor your first CellCog task in a session, read the **cellcog** skill for the full SDK reference — file handling, chat modes, timeouts, and more.\n\n**OpenClaw (fire-and-forget):**\n```python\nresult = client.create_chat(\n    prompt=\"[your task prompt]\",\n    notify_session_key=\"agent:main:main\",\n    task_label=\"my-task\",\n    chat_mode=\"agent\",\n)\n```\n\n**All agents except OpenClaw (blocks until done):**\n```python\nfrom cellcog import CellCogClient\nclient = CellCogClient(agent_provider=\"openclaw|cursor|claude-code|codex|...\")\nresult = client.create_chat(\n    prompt=\"[your task prompt]\",\n    task_label=\"my-task\",\n    chat_mode=\"agent\",\n)\nprint(result[\"message\"])\n```\n\n\n---\n\n## What Financial Work You Can Do\n\n### Stock & Equity Analysis\n\nDeep dives into public companies:\n\n- **Company Analysis**: \"Analyze NVIDIA — revenue trends, margins, competitive moat, and forward guidance\"\n- **Earnings Breakdowns**: \"Break down Apple's Q4 2025 earnings — beat/miss, segment performance, management commentary\"\n- **Valuation Models**: \"Build a DCF model for Microsoft with bear, base, and bull scenarios\"\n- **Peer Comparisons**: \"Compare semiconductor stocks — NVDA, AMD, INTC, TSM — on valuation, growth, and profitability metrics\"\n- **Technical Analysis**: \"Analyze Tesla's price action — key support/resistance levels, moving averages, and volume trends\"\n\n**Example prompt:**\n> \"Create a comprehensive stock analysis for Palantir (PLTR):\n> \n> Cover:\n> - Business model and revenue breakdown (government vs commercial)\n> - Last 4 quarters earnings performance\n> - Key financial metrics (P/E, P/S, FCF margin, revenue growth)\n> - Competitive positioning vs Snowflake, Databricks, C3.ai\n> - Bull and bear thesis\n> - Valuation assessment\n> \n> Deliver as an interactive HTML report with charts.\"\n\n### Portfolio Analysis & Optimization\n\nManage and optimize investments:\n\n- **Portfolio Review**: \"Analyze my portfolio: 40% AAPL, 20% MSFT, 15% GOOGL, 15% AMZN, 10% TSLA — diversification, risk, and recommendations\"\n- **Asset Allocation**: \"Design an optimal portfolio for a 35-year-old with $200K, moderate risk tolerance\"\n- **Risk Assessment**: \"Calculate the Sharpe ratio, beta, and maximum drawdown for this portfolio over the last 3 years\"\n- **Rebalancing**: \"My portfolio drifted from target — recommend rebalancing trades to minimize tax impact\"\n\n### Financial Modeling\n\nBuild professional financial models:\n\n- **DCF Models**: \"Build a discounted cash flow model for Shopify with sensitivity analysis on growth and discount rate\"\n- **Startup Financial Models**: \"Create a 3-year financial projection for a B2B SaaS with $50K MRR growing 15% monthly\"\n- **LBO Models**: \"Model a leveraged buyout scenario for a $100M revenue company at 8x EBITDA\"\n- **Scenario Analysis**: \"Create a 3-scenario model (recession, baseline, boom) for a retail REIT portfolio\"\n\n### Financial Documents & Reports\n\nProfessional financial deliverables:\n\n- **Investment Memos**: \"Write an investment memo recommending a position in CrowdStrike\"\n- **Quarterly Reports**: \"Create a quarterly financial report for my small business\"\n- **Financial Statements**: \"Generate pro forma financial statements for a startup fundraise\"\n- **Tax Planning**: \"Analyze tax optimization strategies for a freelancer earning $150K with $30K in capital gains\"\n\n### Personal Finance\n\nEveryday financial planning:\n\n- **Retirement Planning**: \"How much do I need to save monthly to retire at 55 with $2M? I'm 30, saving $2K/month currently\"\n- **Mortgage Analysis**: \"Compare a 15-year vs 30-year mortgage on a $500K home with 20% down at current rates\"\n- **Debt Payoff**: \"Create a debt payoff plan: $15K student loans at 5%, $8K credit card at 22%, $25K car loan at 6%\"\n- **Budget Optimization**: \"Analyze my spending breakdown and recommend where to cut to save $1,000/month more\"\n\n---\n\n## Output Formats\n\nCellCog delivers financial analysis in multiple formats:\n\n| Format | Best For |\n|--------|----------|\n| **Interactive HTML Dashboard** | Explorable charts, drill-down analysis, live data presentation |\n| **PDF Report** | Shareable, printable investment memos and reports |\n| **XLSX Spreadsheet** | Editable financial models, projections, calculations |\n| **Markdown** | Quick analysis for integration into your docs |\n\nSpecify your preferred format in the prompt:\n- \"Deliver as an interactive HTML report with charts\"\n- \"Create a PDF investment memo\"\n- \"Build this as an editable Excel model\"\n\n---\n\n## Chat Mode for Finance\n\n| Scenario | Recommended Mode |\n|----------|------------------|\n| Quick lookups, single stock metrics, basic calculations | `\"agent\"` |\n| Deep analysis, valuation models, multi-company comparisons, investment research | `\"agent team\"` |\n| High-stakes investment decisions, M&A due diligence, institutional-grade research | `\"agent team max\"` |\n\n**Use `\"agent team\"` for most financial analysis.** Financial work demands deep reasoning, data cross-referencing, and multi-source synthesis. Agent team mode delivers the depth that serious financial analysis requires.\n\n**Use `\"agent\"` for quick financial lookups** — current stock price, simple calculations, or basic metric checks.\n\n**Use `\"agent team max\"` for high-stakes financial work** — investment decisions with significant capital at risk, M&A due diligence, regulatory filings, or boardroom-ready deliverables where the extra reasoning depth justifies the cost. Requires ≥2,000 credits.\n\n---\n\n## Example Prompts\n\n**Comprehensive stock analysis:**\n> \"Create a full investment analysis for AMD:\n> \n> 1. Business Overview — segments, revenue mix, competitive positioning\n> 2. Financial Performance — last 8 quarters revenue, margins, EPS trends\n> 3. Valuation — P/E, P/S, PEG vs peers (NVDA, INTC, QCOM)\n> 4. Growth Catalysts — AI/datacenter, gaming, embedded\n> 5. Risk Factors — competition, cyclicality, customer concentration\n> 6. Bull/Bear/Base price targets\n> \n> Interactive HTML report with comparison charts.\"\n\n**Financial model:**\n> \"Build a startup financial model:\n> \n> Business: B2B SaaS, project management tool\n> Current: $30K MRR, 200 customers, $150 ARPU\n> Growth: 12% MoM for 12 months, then 8% for next 12\n> Team: 8 people now, hiring 4 in next year\n> Expenses: $180K/month burn rate\n> \n> Create a 24-month projection showing:\n> - Revenue forecast with cohort analysis\n> - Expense breakdown and hiring plan\n> - Cash flow and runway\n> - Unit economics (CAC, LTV, payback period)\n> - Break-even analysis\n> \n> Deliver as Excel spreadsheet with charts.\"\n\n**Personal finance:**\n> \"I'm 28, earning $120K/year in San Francisco. I want to:\n> 1. Max out 401K contributions\n> 2. Build a 6-month emergency fund ($30K)\n> 3. Save for a house down payment ($100K in 5 years)\n> 4. Start investing in index funds\n> \n> Create a detailed monthly financial plan that shows how to prioritize these goals with my take-home pay after taxes. Include a timeline and visual roadmap.\"\n\n**Earnings analysis:**\n> \"Break down Tesla's most recent quarterly earnings:\n> \n> - Revenue vs estimates (beat/miss by how much?)\n> - Automotive margins — trend over last 4 quarters\n> - Energy and services segment performance\n> - Key quotes from management on guidance\n> - What analysts are saying post-earnings\n> - Bull and bear reactions\n> \n> Deliver as a concise PDF report with charts.\"\n\n---\n\n## Tips for Better Financial Analysis\n\n1. **Be specific about metrics**: \"Revenue growth\" is vague. \"YoY revenue growth for the last 8 quarters with segment breakdown\" is precise.\n\n2. **Specify time horizons**: \"Analyze AAPL\" is open-ended. \"Analyze AAPL's performance and outlook for the next 12 months\" is actionable.\n\n3. **State your purpose**: \"For an investment decision\", \"For a board presentation\", \"For personal planning\" — context shapes the analysis.\n\n4. **Include constraints**: Budget, risk tolerance, time horizon, tax situation — these matter for financial recommendations.\n\n5. **Request scenarios**: \"Include bear, base, and bull cases\" gives you a range, not just a point estimate.\n\n6. **Ask for the deliverable you need**: \"Interactive dashboard\", \"PDF memo\", \"Excel model\" — specify the format for the best result.\n\n---\n\n## If CellCog is not installed\n\nRun `/cellcog-setup` (or `/cellcog:cellcog-setup` depending on your tool) to install and authenticate.\n**OpenClaw users:** Run `clawhub install cellcog` instead.\n**Manual setup:** `pip install -U cellcog` and set `CELLCOG_API_KEY`. See the **cellcog** skill for SDK reference.\n\nFile v1.0.12:_meta.json\n\n{\n  \"ownerId\": \"kn7a96cj9q65e0bhmzahv790en80ffqm\",\n  \"slug\": \"stock-analysis-cellcog\",\n  \"version\": \"1.0.12\",\n  \"publishedAt\": 1776925133825\n}\n\nFile v1.0.12:skill-card.md\n\n## Description: <br>\nAI financial analysis and stock research powered by CellCog for stock analysis, valuation models, portfolio optimization, earnings breakdowns, investment research, financial statements, tax planning, and DCF modeling. <br>\n\nThis skill is ready for commercial/non-commercial use. <br>\n\n## Publisher: <br>\n[nitishgargiitd](https://clawhub.ai/user/nitishgargiitd) <br>\n\n### License/Terms of Use: <br>\nMIT-0 <br>\n\n\n## Use Case: <br>\nDevelopers, analysts, and agents use this skill to request CellCog-powered financial analysis, stock research, valuation models, portfolio optimization, tax planning, and investment or personal finance reports. <br>\n\n### Deployment Geography for Use: <br>\nGlobal <br>\n\n## Known Risks and Mitigations: <br>\nRisk: Users may include sensitive personal financial details in prompts. <br>\nMitigation: Avoid sending account numbers, SSNs, full tax documents, exact addresses, or unnecessary identifiers; use redacted or aggregated figures where possible. <br>\nRisk: Financial outputs may be mistaken for licensed investment, tax, or financial advice. <br>\nMitigation: Treat outputs as research support and have qualified professionals review high-stakes investment, tax, regulatory, or board-level decisions. <br>\n\n\n## Reference(s): <br>\n- [Fin Cog on ClawHub](https://clawhub.ai/nitishgargiitd/skills/fin-cog) <br>\n- [CellCog homepage](https://cellcog.ai) <br>\n\n\n## Skill Output: <br>\n**Output Type(s):** [text, markdown, code, shell commands, configuration, guidance] <br>\n**Output Format:** [Markdown guidance with Python examples; CellCog tasks may return Markdown, interactive HTML dashboards, PDF reports, or XLSX models.] <br>\n**Output Parameters:** [1D] <br>\n**Other Properties Related to Output:** [Requires python3 and CELLCOG_API_KEY; supports darwin, linux, and windows.] <br>\n\n## Skill Version(s): <br>\n1.0.12 (source: server release metadata) <br>\n\n## Ethical Considerations: <br>\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment. <br>\n\nArchive v1.0.11: 2 files, 4640 bytes\n\nFiles: SKILL.md (9515b), _meta.json (142b)\n\nFile v1.0.11:SKILL.md\n\n---\nname: fin-cog\ndescription: \"AI financial analysis and stock research powered by CellCog. Stock analysis, valuation models, portfolio optimization, earnings breakdowns, investment research, financial statements, tax planning, DCF modeling. Deliverables as interactive dashboards, PDF reports, and Excel models.\"\nmetadata:\n  openclaw:\n    emoji: \"💰\"\n    os: [darwin, linux, windows]\nauthor: CellCog\nhomepage: https://cellcog.ai\ndependencies: [cellcog]\n---\n# Fin Cog - Wall Street-Grade Analysis, Accessible Globally\n\n**Wall Street-grade analysis, accessible globally.** Deep financial reasoning powered by #1 on DeepResearch Bench (Apr 2026) + SOTA financial models.\n\nThe best financial analysis has always lived behind Bloomberg terminals, institutional research desks, and $500/hour consultants. CellCog brings that same depth — stock analysis, valuation models, portfolio optimization, earnings breakdowns — to anyone with a prompt. From raw tickers to boardroom-ready deliverables in one request.\n\n## How to Use\n\nFor your first CellCog task in a session, read the **cellcog** skill for the full SDK reference — file handling, chat modes, timeouts, and more.\n\n**OpenClaw (fire-and-forget):**\n```python\nresult = client.create_chat(\n    prompt=\"[your task prompt]\",\n    notify_session_key=\"agent:main:main\",\n    task_label=\"my-task\",\n    chat_mode=\"agent\",\n)\n```\n\n**All agents except OpenClaw (blocks until done):**\n```python\nfrom cellcog import CellCogClient\nclient = CellCogClient(agent_provider=\"openclaw|cursor|claude-code|codex|...\")\nresult = client.create_chat(\n    prompt=\"[your task prompt]\",\n    task_label=\"my-task\",\n    chat_mode=\"agent\",\n)\nprint(result[\"message\"])\n```\n\n\n---\n\n## What Financial Work You Can Do\n\n### Stock & Equity Analysis\n\nDeep dives into public companies:\n\n- **Company Analysis**: \"Analyze NVIDIA — revenue trends, margins, competitive moat, and forward guidance\"\n- **Earnings Breakdowns**: \"Break down Apple's Q4 2025 earnings — beat/miss, segment performance, management commentary\"\n- **Valuation Models**: \"Build a DCF model for Microsoft with bear, base, and bull scenarios\"\n- **Peer Comparisons**: \"Compare semiconductor stocks — NVDA, AMD, INTC, TSM — on valuation, growth, and profitability metrics\"\n- **Technical Analysis**: \"Analyze Tesla's price action — key support/resistance levels, moving averages, and volume trends\"\n\n**Example prompt:**\n> \"Create a comprehensive stock analysis for Palantir (PLTR):\n> \n> Cover:\n> - Business model and revenue breakdown (government vs commercial)\n> - Last 4 quarters earnings performance\n> - Key financial metrics (P/E, P/S, FCF margin, revenue growth)\n> - Competitive positioning vs Snowflake, Databricks, C3.ai\n> - Bull and bear thesis\n> - Valuation assessment\n> \n> Deliver as an interactive HTML report with charts.\"\n\n### Portfolio Analysis & Optimization\n\nManage and optimize investments:\n\n- **Portfolio Review**: \"Analyze my portfolio: 40% AAPL, 20% MSFT, 15% GOOGL, 15% AMZN, 10% TSLA — diversification, risk, and recommendations\"\n- **Asset Allocation**: \"Design an optimal portfolio for a 35-year-old with $200K, moderate risk tolerance\"\n- **Risk Assessment**: \"Calculate the Sharpe ratio, beta, and maximum drawdown for this portfolio over the last 3 years\"\n- **Rebalancing**: \"My portfolio drifted from target — recommend rebalancing trades to minimize tax impact\"\n\n### Financial Modeling\n\nBuild professional financial models:\n\n- **DCF Models**: \"Build a discounted cash flow model for Shopify with sensitivity analysis on growth and discount rate\"\n- **Startup Financial Models**: \"Create a 3-year financial projection for a B2B SaaS with $50K MRR growing 15% monthly\"\n- **LBO Models**: \"Model a leveraged buyout scenario for a $100M revenue company at 8x EBITDA\"\n- **Scenario Analysis**: \"Create a 3-scenario model (recession, baseline, boom) for a retail REIT portfolio\"\n\n### Financial Documents & Reports\n\nProfessional financial deliverables:\n\n- **Investment Memos**: \"Write an investment memo recommending a position in CrowdStrike\"\n- **Quarterly Reports**: \"Create a quarterly financial report for my small business\"\n- **Financial Statements**: \"Generate pro forma financial statements for a startup fundraise\"\n- **Tax Planning**: \"Analyze tax optimization strategies for a freelancer earning $150K with $30K in capital gains\"\n\n### Personal Finance\n\nEveryday financial planning:\n\n- **Retirement Planning**: \"How much do I need to save monthly to retire at 55 with $2M? I'm 30, saving $2K/month currently\"\n- **Mortgage Analysis**: \"Compare a 15-year vs 30-year mortgage on a $500K home with 20% down at current rates\"\n- **Debt Payoff**: \"Create a debt payoff plan: $15K student loans at 5%, $8K credit card at 22%, $25K car loan at 6%\"\n- **Budget Optimization**: \"Analyze my spending breakdown and recommend where to cut to save $1,000/month more\"\n\n---\n\n## Output Formats\n\nCellCog delivers financial analysis in multiple formats:\n\n| Format | Best For |\n|--------|----------|\n| **Interactive HTML Dashboard** | Explorable charts, drill-down analysis, live data presentation |\n| **PDF Report** | Shareable, printable investment memos and reports |\n| **XLSX Spreadsheet** | Editable financial models, projections, calculations |\n| **Markdown** | Quick analysis for integration into your docs |\n\nSpecify your preferred format in the prompt:\n- \"Deliver as an interactive HTML report with charts\"\n- \"Create a PDF investment memo\"\n- \"Build this as an editable Excel model\"\n\n---\n\n## Chat Mode for Finance\n\n| Scenario | Recommended Mode |\n|----------|------------------|\n| Quick lookups, single stock metrics, basic calculations | `\"agent\"` |\n| Deep analysis, valuation models, multi-company comparisons, investment research | `\"agent team\"` |\n| High-stakes investment decisions, M&A due diligence, institutional-grade research | `\"agent team max\"` |\n\n**Use `\"agent team\"` for most financial analysis.** Financial work demands deep reasoning, data cross-referencing, and multi-source synthesis. Agent team mode delivers the depth that serious financial analysis requires.\n\n**Use `\"agent\"` for quick financial lookups** — current stock price, simple calculations, or basic metric checks.\n\n**Use `\"agent team max\"` for high-stakes financial work** — investment decisions with significant capital at risk, M&A due diligence, regulatory filings, or boardroom-ready deliverables where the extra reasoning depth justifies the cost. Requires ≥2,000 credits.\n\n---\n\n## Example Prompts\n\n**Comprehensive stock analysis:**\n> \"Create a full investment analysis for AMD:\n> \n> 1. Business Overview — segments, revenue mix, competitive positioning\n> 2. Financial Performance — last 8 quarters revenue, margins, EPS trends\n> 3. Valuation — P/E, P/S, PEG vs peers (NVDA, INTC, QCOM)\n> 4. Growth Catalysts — AI/datacenter, gaming, embedded\n> 5. Risk Factors — competition, cyclicality, customer concentration\n> 6. Bull/Bear/Base price targets\n> \n> Interactive HTML report with comparison charts.\"\n\n**Financial model:**\n> \"Build a startup financial model:\n> \n> Business: B2B SaaS, project management tool\n> Current: $30K MRR, 200 customers, $150 ARPU\n> Growth: 12% MoM for 12 months, then 8% for next 12\n> Team: 8 people now, hiring 4 in next year\n> Expenses: $180K/month burn rate\n> \n> Create a 24-month projection showing:\n> - Revenue forecast with cohort analysis\n> - Expense breakdown and hiring plan\n> - Cash flow and runway\n> - Unit economics (CAC, LTV, payback period)\n> - Break-even analysis\n> \n> Deliver as Excel spreadsheet with charts.\"\n\n**Personal finance:**\n> \"I'm 28, earning $120K/year in San Francisco. I want to:\n> 1. Max out 401K contributions\n> 2. Build a 6-month emergency fund ($30K)\n> 3. Save for a house down payment ($100K in 5 years)\n> 4. Start investing in index funds\n> \n> Create a detailed monthly financial plan that shows how to prioritize these goals with my take-home pay after taxes. Include a timeline and visual roadmap.\"\n\n**Earnings analysis:**\n> \"Break down Tesla's most recent quarterly earnings:\n> \n> - Revenue vs estimates (beat/miss by how much?)\n> - Automotive margins — trend over last 4 quarters\n> - Energy and services segment performance\n> - Key quotes from management on guidance\n> - What analysts are saying post-earnings\n> - Bull and bear reactions\n> \n> Deliver as a concise PDF report with charts.\"\n\n---\n\n## Tips for Better Financial Analysis\n\n1. **Be specific about metrics**: \"Revenue growth\" is vague. \"YoY revenue growth for the last 8 quarters with segment breakdown\" is precise.\n\n2. **Specify time horizons**: \"Analyze AAPL\" is open-ended. \"Analyze AAPL's performance and outlook for the next 12 months\" is actionable.\n\n3. **State your purpose**: \"For an investment decision\", \"For a board presentation\", \"For personal planning\" — context shapes the analysis.\n\n4. **Include constraints**: Budget, risk tolerance, time horizon, tax situation — these matter for financial recommendations.\n\n5. **Request scenarios**: \"Include bear, base, and bull cases\" gives you a range, not just a point estimate.\n\n6. **Ask for the deliverable you need**: \"Interactive dashboard\", \"PDF memo\", \"Excel model\" — specify the format for the best result.\n\n---\n\n## If CellCog is not installed\n\nRun `/cellcog-setup` (or `/cellcog:cellcog-setup` depending on your tool) to install and authenticate.\n**OpenClaw users:** Run `clawhub install cellcog` instead.\n**Manual setup:** `pip install -U cellcog` and set `CELLCOG_API_KEY`. See the **cellcog** skill for SDK reference.\n\nFile v1.0.11:_meta.json\n\n{\n  \"ownerId\": \"kn7a96cj9q65e0bhmzahv790en80ffqm\",\n  \"slug\": \"stock-analysis-cellcog\",\n  \"version\": \"1.0.11\",\n  \"publishedAt\": 1776187938069\n}\n\nArchive v1.0.10: 2 files, 4627 bytes\n\nFiles: SKILL.md (9539b), _meta.json (142b)\n\nFile v1.0.10:SKILL.md\n\n---\nname: fin-cog\ndescription: \"AI financial analysis and stock research powered by CellCog. Stock analysis, valuation models, portfolio optimization, earnings breakdowns, investment research, financial statements, tax planning, and DCF modeling. Wall Street-grade deliverables — interactive dashboards, PDF reports, Excel models. #1 on DeepResearch Bench (Apr 2026).\"\nmetadata:\n  openclaw:\n    emoji: \"💰\"\n    os: [darwin, linux, windows]\nauthor: CellCog\nhomepage: https://cellcog.ai\ndependencies: [cellcog]\n---\n# Fin Cog - Wall Street-Grade Analysis, Accessible Globally\n\n**Wall Street-grade analysis, accessible globally.** Deep financial reasoning powered by #1 on DeepResearch Bench (Apr 2026) + SOTA financial models.\n\nThe best financial analysis has always lived behind Bloomberg terminals, institutional research desks, and $500/hour consultants. CellCog brings that same depth — stock analysis, valuation models, portfolio optimization, earnings breakdowns — to anyone with a prompt. From raw tickers to boardroom-ready deliverables in one request.\n\n## How to Use\n\nFor your first CellCog task in a session, read the **cellcog** skill for the full SDK reference — file handling, chat modes, timeouts, and more.\n\n**OpenClaw (fire-and-forget):**\n```python\nresult = client.create_chat(\n    prompt=\"[your task prompt]\",\n    notify_session_key=\"agent:main:main\",\n    task_label=\"my-task\",\n    chat_mode=\"agent\",\n)\n```\n\n**Cursor / Claude Code / Other agents (blocks until done):**\n```python\nfrom cellcog import CellCogClient\nclient = CellCogClient(agent_provider=\"openclaw|cursor|claude-code|codex|...\")\nresult = client.create_chat(\n    prompt=\"[your task prompt]\",\n    task_label=\"my-task\",\n    chat_mode=\"agent\",\n)\nprint(result[\"message\"])\n```\n\n\n---\n\n## What Financial Work You Can Do\n\n### Stock & Equity Analysis\n\nDeep dives into public companies:\n\n- **Company Analysis**: \"Analyze NVIDIA — revenue trends, margins, competitive moat, and forward guidance\"\n- **Earnings Breakdowns**: \"Break down Apple's Q4 2025 earnings — beat/miss, segment performance, management commentary\"\n- **Valuation Models**: \"Build a DCF model for Microsoft with bear, base, and bull scenarios\"\n- **Peer Comparisons**: \"Compare semiconductor stocks — NVDA, AMD, INTC, TSM — on valuation, growth, and profitability metrics\"\n- **Technical Analysis**: \"Analyze Tesla's price action — key support/resistance levels, moving averages, and volume trends\"\n\n**Example prompt:**\n> \"Create a comprehensive stock analysis for Palantir (PLTR):\n> \n> Cover:\n> - Business model and revenue breakdown (government vs commercial)\n> - Last 4 quarters earnings performance\n> - Key financial metrics (P/E, P/S, FCF margin, revenue growth)\n> - Competitive positioning vs Snowflake, Databricks, C3.ai\n> - Bull and bear thesis\n> - Valuation assessment\n> \n> Deliver as an interactive HTML report with charts.\"\n\n### Portfolio Analysis & Optimization\n\nManage and optimize investments:\n\n- **Portfolio Review**: \"Analyze my portfolio: 40% AAPL, 20% MSFT, 15% GOOGL, 15% AMZN, 10% TSLA — diversification, risk, and recommendations\"\n- **Asset Allocation**: \"Design an optimal portfolio for a 35-year-old with $200K, moderate risk tolerance\"\n- **Risk Assessment**: \"Calculate the Sharpe ratio, beta, and maximum drawdown for this portfolio over the last 3 years\"\n- **Rebalancing**: \"My portfolio drifted from target — recommend rebalancing trades to minimize tax impact\"\n\n### Financial Modeling\n\nBuild professional financial models:\n\n- **DCF Models**: \"Build a discounted cash flow model for Shopify with sensitivity analysis on growth and discount rate\"\n- **Startup Financial Models**: \"Create a 3-year financial projection for a B2B SaaS with $50K MRR growing 15% monthly\"\n- **LBO Models**: \"Model a leveraged buyout scenario for a $100M revenue company at 8x EBITDA\"\n- **Scenario Analysis**: \"Create a 3-scenario model (recession, baseline, boom) for a retail REIT portfolio\"\n\n### Financial Documents & Reports\n\nProfessional financial deliverables:\n\n- **Investment Memos**: \"Write an investment memo recommending a position in CrowdStrike\"\n- **Quarterly Reports**: \"Create a quarterly financial report for my small business\"\n- **Financial Statements**: \"Generate pro forma financial statements for a startup fundraise\"\n- **Tax Planning**: \"Analyze tax optimization strategies for a freelancer earning $150K with $30K in capital gains\"\n\n### Personal Finance\n\nEveryday financial planning:\n\n- **Retirement Planning**: \"How much do I need to save monthly to retire at 55 with $2M? I'm 30, saving $2K/month currently\"\n- **Mortgage Analysis**: \"Compare a 15-year vs 30-year mortgage on a $500K home with 20% down at current rates\"\n- **Debt Payoff**: \"Create a debt payoff plan: $15K student loans at 5%, $8K credit card at 22%, $25K car loan at 6%\"\n- **Budget Optimization**: \"Analyze my spending breakdown and recommend where to cut to save $1,000/month more\"\n\n---\n\n## Output Formats\n\nCellCog delivers financial analysis in multiple formats:\n\n| Format | Best For |\n|--------|----------|\n| **Interactive HTML Dashboard** | Explorable charts, drill-down analysis, live data presentation |\n| **PDF Report** | Shareable, printable investment memos and reports |\n| **XLSX Spreadsheet** | Editable financial models, projections, calculations |\n| **Markdown** | Quick analysis for integration into your docs |\n\nSpecify your preferred format in the prompt:\n- \"Deliver as an interactive HTML report with charts\"\n- \"Create a PDF investment memo\"\n- \"Build this as an editable Excel model\"\n\n---\n\n## Chat Mode for Finance\n\n| Scenario | Recommended Mode |\n|----------|------------------|\n| Quick lookups, single stock metrics, basic calculations | `\"agent\"` |\n| Deep analysis, valuation models, multi-company comparisons, investment research | `\"agent team\"` |\n| High-stakes investment decisions, M&A due diligence, institutional-grade research | `\"agent team max\"` |\n\n**Use `\"agent team\"` for most financial analysis.** Financial work demands deep reasoning, data cross-referencing, and multi-source synthesis. Agent team mode delivers the depth that serious financial analysis requires.\n\n**Use `\"agent\"` for quick financial lookups** — current stock price, simple calculations, or basic metric checks.\n\n**Use `\"agent team max\"` for high-stakes financial work** — investment decisions with significant capital at risk, M&A due diligence, regulatory filings, or boardroom-ready deliverables where the extra reasoning depth justifies the cost. Requires ≥2,000 credits.\n\n---\n\n## Example Prompts\n\n**Comprehensive stock analysis:**\n> \"Create a full investment analysis for AMD:\n> \n> 1. Business Overview — segments, revenue mix, competitive positioning\n> 2. Financial Performance — last 8 quarters revenue, margins, EPS trends\n> 3. Valuation — P/E, P/S, PEG vs peers (NVDA, INTC, QCOM)\n> 4. Growth Catalysts — AI/datacenter, gaming, embedded\n> 5. Risk Factors — competition, cyclicality, customer concentration\n> 6. Bull/Bear/Base price targets\n> \n> Interactive HTML report with comparison charts.\"\n\n**Financial model:**\n> \"Build a startup financial model:\n> \n> Business: B2B SaaS, project management tool\n> Current: $30K MRR, 200 customers, $150 ARPU\n> Growth: 12% MoM for 12 months, then 8% for next 12\n> Team: 8 people now, hiring 4 in next year\n> Expenses: $180K/month burn rate\n> \n> Create a 24-month projection showing:\n> - Revenue forecast with cohort analysis\n> - Expense breakdown and hiring plan\n> - Cash flow and runway\n> - Unit economics (CAC, LTV, payback period)\n> - Break-even analysis\n> \n> Deliver as Excel spreadsheet with charts.\"\n\n**Personal finance:**\n> \"I'm 28, earning $120K/year in San Francisco. I want to:\n> 1. Max out 401K contributions\n> 2. Build a 6-month emergency fund ($30K)\n> 3. Save for a house down payment ($100K in 5 years)\n> 4. Start investing in index funds\n> \n> Create a detailed monthly financial plan that shows how to prioritize these goals with my take-home pay after taxes. Include a timeline and visual roadmap.\"\n\n**Earnings analysis:**\n> \"Break down Tesla's most recent quarterly earnings:\n> \n> - Revenue vs estimates (beat/miss by how much?)\n> - Automotive margins — trend over last 4 quarters\n> - Energy and services segment performance\n> - Key quotes from management on guidance\n> - What analysts are saying post-earnings\n> - Bull and bear reactions\n> \n> Deliver as a concise PDF report with charts.\"\n\n---\n\n## Tips for Better Financial Analysis\n\n1. **Be specific about metrics**: \"Revenue growth\" is vague. \"YoY revenue growth for the last 8 quarters with segment breakdown\" is precise.\n\n2. **Specify time horizons**: \"Analyze AAPL\" is open-ended. \"Analyze AAPL's performance and outlook for the next 12 months\" is actionable.\n\n3. **State your purpose**: \"For an investment decision\", \"For a board presentation\", \"For personal planning\" — context shapes the analysis.\n\n4. **Include constraints**: Budget, risk tolerance, time horizon, tax situation — these matter for financial recommendations.\n\n5. **Request scenarios**: \"Include bear, base, and bull cases\" gives you a range, not just a point estimate.\n\n6. **Ask for the deliverable you need**: \"Interactive dashboard\", \"PDF memo\", \"Excel model\" — specify the format for the best result.\n\n---\n\n## If CellCog is not installed\n\n**Cursor:** Run `/cellcog-setup` to install and authenticate.\n**OpenClaw:** Run `clawhub install cellcog` for SDK setup.\n**Other agents:** `pip install -U cellcog` and set `CELLCOG_API_KEY`. See the **cellcog** skill for SDK reference.\n\nFile v1.0.10:_meta.json\n\n{\n  \"ownerId\": \"kn7a96cj9q65e0bhmzahv790en80ffqm\",\n  \"slug\": \"stock-analysis-cellcog\",\n  \"version\": \"1.0.10\",\n  \"publishedAt\": 1776042048992\n}\n\nArchive v1.0.9: 2 files, 4559 bytes\n\nFiles: SKILL.md (9325b), _meta.json (141b)\n\nFile v1.0.9:SKILL.md\n\n---\nname: fin-cog\ndescription: \"Powered by CellCog. Financial analysis and stock research. Valuation models, portfolio optimization, earnings breakdowns, investment research, financial statements, and DCF modeling. Interactive dashboards, PDF reports, or Excel output.\"\nmetadata:\n  openclaw:\n    emoji: \"💰\"\n    os: [darwin, linux, windows]\nauthor: CellCog\nhomepage: https://cellcog.ai\ndependencies: [cellcog]\n---\n# Fin Cog - Wall Street-Grade Analysis, Accessible Globally\n\n**Wall Street-grade analysis, accessible globally.** Deep financial reasoning powered by #1 on DeepResearch Bench (Apr 2026) + SOTA financial models.\n\nThe best financial analysis has always lived behind Bloomberg terminals, institutional research desks, and $500/hour consultants. CellCog brings that same depth — stock analysis, valuation models, portfolio optimization, earnings breakdowns — to anyone with a prompt. From raw tickers to boardroom-ready deliverables in one request.\n\n## How to Use\n\nFor your first CellCog task in a session, read the **cellcog** skill for the full SDK reference — file handling, chat modes, timeouts, and more.\n\n**OpenClaw (fire-and-forget):**\n```python\nresult = client.create_chat(\n    prompt=\"[your task prompt]\",\n    notify_session_key=\"agent:main:main\",\n    task_label=\"my-task\",\n    chat_mode=\"agent\",\n)\n```\n\n**Cursor / Claude Code / Other agents (blocks until done):**\n```python\nresult = client.create_chat(\n    prompt=\"[your task prompt]\",\n    task_label=\"my-task\",\n    chat_mode=\"agent\",\n)\nprint(result[\"message\"])\n```\n\n\n---\n\n## What Financial Work You Can Do\n\n### Stock & Equity Analysis\n\nDeep dives into public companies:\n\n- **Company Analysis**: \"Analyze NVIDIA — revenue trends, margins, competitive moat, and forward guidance\"\n- **Earnings Breakdowns**: \"Break down Apple's Q4 2025 earnings — beat/miss, segment performance, management commentary\"\n- **Valuation Models**: \"Build a DCF model for Microsoft with bear, base, and bull scenarios\"\n- **Peer Comparisons**: \"Compare semiconductor stocks — NVDA, AMD, INTC, TSM — on valuation, growth, and profitability metrics\"\n- **Technical Analysis**: \"Analyze Tesla's price action — key support/resistance levels, moving averages, and volume trends\"\n\n**Example prompt:**\n> \"Create a comprehensive stock analysis for Palantir (PLTR):\n> \n> Cover:\n> - Business model and revenue breakdown (government vs commercial)\n> - Last 4 quarters earnings performance\n> - Key financial metrics (P/E, P/S, FCF margin, revenue growth)\n> - Competitive positioning vs Snowflake, Databricks, C3.ai\n> - Bull and bear thesis\n> - Valuation assessment\n> \n> Deliver as an interactive HTML report with charts.\"\n\n### Portfolio Analysis & Optimization\n\nManage and optimize investments:\n\n- **Portfolio Review**: \"Analyze my portfolio: 40% AAPL, 20% MSFT, 15% GOOGL, 15% AMZN, 10% TSLA — diversification, risk, and recommendations\"\n- **Asset Allocation**: \"Design an optimal portfolio for a 35-year-old with $200K, moderate risk tolerance\"\n- **Risk Assessment**: \"Calculate the Sharpe ratio, beta, and maximum drawdown for this portfolio over the last 3 years\"\n- **Rebalancing**: \"My portfolio drifted from target — recommend rebalancing trades to minimize tax impact\"\n\n### Financial Modeling\n\nBuild professional financial models:\n\n- **DCF Models**: \"Build a discounted cash flow model for Shopify with sensitivity analysis on growth and discount rate\"\n- **Startup Financial Models**: \"Create a 3-year financial projection for a B2B SaaS with $50K MRR growing 15% monthly\"\n- **LBO Models**: \"Model a leveraged buyout scenario for a $100M revenue company at 8x EBITDA\"\n- **Scenario Analysis**: \"Create a 3-scenario model (recession, baseline, boom) for a retail REIT portfolio\"\n\n### Financial Documents & Reports\n\nProfessional financial deliverables:\n\n- **Investment Memos**: \"Write an investment memo recommending a position in CrowdStrike\"\n- **Quarterly Reports**: \"Create a quarterly financial report for my small business\"\n- **Financial Statements**: \"Generate pro forma financial statements for a startup fundraise\"\n- **Tax Planning**: \"Analyze tax optimization strategies for a freelancer earning $150K with $30K in capital gains\"\n\n### Personal Finance\n\nEveryday financial planning:\n\n- **Retirement Planning**: \"How much do I need to save monthly to retire at 55 with $2M? I'm 30, saving $2K/month currently\"\n- **Mortgage Analysis**: \"Compare a 15-year vs 30-year mortgage on a $500K home with 20% down at current rates\"\n- **Debt Payoff**: \"Create a debt payoff plan: $15K student loans at 5%, $8K credit card at 22%, $25K car loan at 6%\"\n- **Budget Optimization**: \"Analyze my spending breakdown and recommend where to cut to save $1,000/month more\"\n\n---\n\n## Output Formats\n\nCellCog delivers financial analysis in multiple formats:\n\n| Format | Best For |\n|--------|----------|\n| **Interactive HTML Dashboard** | Explorable charts, drill-down analysis, live data presentation |\n| **PDF Report** | Shareable, printable investment memos and reports |\n| **XLSX Spreadsheet** | Editable financial models, projections, calculations |\n| **Markdown** | Quick analysis for integration into your docs |\n\nSpecify your preferred format in the prompt:\n- \"Deliver as an interactive HTML report with charts\"\n- \"Create a PDF investment memo\"\n- \"Build this as an editable Excel model\"\n\n---\n\n## Chat Mode for Finance\n\n| Scenario | Recommended Mode |\n|----------|------------------|\n| Quick lookups, single stock metrics, basic calculations | `\"agent\"` |\n| Deep analysis, valuation models, multi-company comparisons, investment research | `\"agent team\"` |\n| High-stakes investment decisions, M&A due diligence, institutional-grade research | `\"agent team max\"` |\n\n**Use `\"agent team\"` for most financial analysis.** Financial work demands deep reasoning, data cross-referencing, and multi-source synthesis. Agent team mode delivers the depth that serious financial analysis requires.\n\n**Use `\"agent\"` for quick financial lookups** — current stock price, simple calculations, or basic metric checks.\n\n**Use `\"agent team max\"` for high-stakes financial work** — investment decisions with significant capital at risk, M&A due diligence, regulatory filings, or boardroom-ready deliverables where the extra reasoning depth justifies the cost. Requires ≥2,000 credits.\n\n---\n\n## Example Prompts\n\n**Comprehensive stock analysis:**\n> \"Create a full investment analysis for AMD:\n> \n> 1. Business Overview — segments, revenue mix, competitive positioning\n> 2. Financial Performance — last 8 quarters revenue, margins, EPS trends\n> 3. Valuation — P/E, P/S, PEG vs peers (NVDA, INTC, QCOM)\n> 4. Growth Catalysts — AI/datacenter, gaming, embedded\n> 5. Risk Factors — competition, cyclicality, customer concentration\n> 6. Bull/Bear/Base price targets\n> \n> Interactive HTML report with comparison charts.\"\n\n**Financial model:**\n> \"Build a startup financial model:\n> \n> Business: B2B SaaS, project management tool\n> Current: $30K MRR, 200 customers, $150 ARPU\n> Growth: 12% MoM for 12 months, then 8% for next 12\n> Team: 8 people now, hiring 4 in next year\n> Expenses: $180K/month burn rate\n> \n> Create a 24-month projection showing:\n> - Revenue forecast with cohort analysis\n> - Expense breakdown and hiring plan\n> - Cash flow and runway\n> - Unit economics (CAC, LTV, payback period)\n> - Break-even analysis\n> \n> Deliver as Excel spreadsheet with charts.\"\n\n**Personal finance:**\n> \"I'm 28, earning $120K/year in San Francisco. I want to:\n> 1. Max out 401K contributions\n> 2. Build a 6-month emergency fund ($30K)\n> 3. Save for a house down payment ($100K in 5 years)\n> 4. Start investing in index funds\n> \n> Create a detailed monthly financial plan that shows how to prioritize these goals with my take-home pay after taxes. Include a timeline and visual roadmap.\"\n\n**Earnings analysis:**\n> \"Break down Tesla's most recent quarterly earnings:\n> \n> - Revenue vs estimates (beat/miss by how much?)\n> - Automotive margins — trend over last 4 quarters\n> - Energy and services segment performance\n> - Key quotes from management on guidance\n> - What analysts are saying post-earnings\n> - Bull and bear reactions\n> \n> Deliver as a concise PDF report with charts.\"\n\n---\n\n## Tips for Better Financial Analysis\n\n1. **Be specific about metrics**: \"Revenue growth\" is vague. \"YoY revenue growth for the last 8 quarters with segment breakdown\" is precise.\n\n2. **Specify time horizons**: \"Analyze AAPL\" is open-ended. \"Analyze AAPL's performance and outlook for the next 12 months\" is actionable.\n\n3. **State your purpose**: \"For an investment decision\", \"For a board presentation\", \"For personal planning\" — context shapes the analysis.\n\n4. **Include constraints**: Budget, risk tolerance, time horizon, tax situation — these matter for financial recommendations.\n\n5. **Request scenarios**: \"Include bear, base, and bull cases\" gives you a range, not just a point estimate.\n\n6. **Ask for the deliverable you need**: \"Interactive dashboard\", \"PDF memo\", \"Excel model\" — specify the format for the best result.\n\n---\n\n## If CellCog is not installed\n\n**Cursor:** Run `/cellcog-setup` to install and authenticate.\n**OpenClaw:** Run `clawhub install cellcog` for SDK setup.\n**Other agents:** `pip install -U cellcog` and set `CELLCOG_API_KEY`. See the **cellcog** skill for SDK reference.\n\nFile v1.0.9:_meta.json\n\n{\n  \"ownerId\": \"kn7a96cj9q65e0bhmzahv790en80ffqm\",\n  \"slug\": \"stock-analysis-cellcog\",\n  \"version\": \"1.0.9\",\n  \"publishedAt\": 1776036927296\n}\n\nArchive v1.0.8: 2 files, 4525 bytes\n\nFiles: SKILL.md (9377b), _meta.json (141b)\n\nFile v1.0.8:SKILL.md\n\n---\nname: fin-cog\ndescription: \"AI financial analysis and stock research powered by CellCog. Stock analysis, valuation models, portfolio optimization, earnings breakdowns, investment research, financial statements, tax planning, and DCF modeling. Wall Street-grade deliverables — interactive dashboards, PDF reports, Excel models. #1 on DeepResearch Bench (Apr 2026).\"\nmetadata:\n  openclaw:\n    emoji: \"💰\"\n    os: [darwin, linux, windows]\nauthor: CellCog\nhomepage: https://cellcog.ai\ndependencies: [cellcog]\n---\n\n# Fin Cog - Wall Street-Grade Analysis, Accessible Globally\n\n**Wall Street-grade analysis, accessible globally.** Deep financial reasoning powered by #1 on DeepResearch Bench (Apr 2026) + SOTA financial models.\n\nThe best financial analysis has always lived behind Bloomberg terminals, institutional research desks, and $500/hour consultants. CellCog brings that same depth — stock analysis, valuation models, portfolio optimization, earnings breakdowns — to anyone with a prompt. From raw tickers to boardroom-ready deliverables in one request.\n\n---\n\n## Prerequisites\n\nThis skill requires the `cellcog` skill for SDK setup and API calls.\n\n```bash\nclawhub install cellcog\n```\n\n**Read the cellcog skill first** for SDK setup. This skill shows you what's possible.\n\n**OpenClaw agents (fire-and-forget — recommended for long tasks):**\n```python\nresult = client.create_chat(\n    prompt=\"[your task prompt]\",\n    notify_session_key=\"agent:main:main\",  # OpenClaw only\n    task_label=\"my-task\",\n    chat_mode=\"agent\",  # See cellcog skill for all modes\n)\n```\n\n**All other agents (blocks until done):**\n```python\nresult = client.create_chat(\n    prompt=\"[your task prompt]\",\n    task_label=\"my-task\",\n    chat_mode=\"agent\",\n)\n```\n\nSee the **cellcog** mothership skill for complete SDK API reference — delivery modes, timeouts, file handling, and more.\n\n---\n\n## What Financial Work You Can Do\n\n### Stock & Equity Analysis\n\nDeep dives into public companies:\n\n- **Company Analysis**: \"Analyze NVIDIA — revenue trends, margins, competitive moat, and forward guidance\"\n- **Earnings Breakdowns**: \"Break down Apple's Q4 2025 earnings — beat/miss, segment performance, management commentary\"\n- **Valuation Models**: \"Build a DCF model for Microsoft with bear, base, and bull scenarios\"\n- **Peer Comparisons**: \"Compare semiconductor stocks — NVDA, AMD, INTC, TSM — on valuation, growth, and profitability metrics\"\n- **Technical Analysis**: \"Analyze Tesla's price action — key support/resistance levels, moving averages, and volume trends\"\n\n**Example prompt:**\n> \"Create a comprehensive stock analysis for Palantir (PLTR):\n> \n> Cover:\n> - Business model and revenue breakdown (government vs commercial)\n> - Last 4 quarters earnings performance\n> - Key financial metrics (P/E, P/S, FCF margin, revenue growth)\n> - Competitive positioning vs Snowflake, Databricks, C3.ai\n> - Bull and bear thesis\n> - Valuation assessment\n> \n> Deliver as an interactive HTML report with charts.\"\n\n### Portfolio Analysis & Optimization\n\nManage and optimize investments:\n\n- **Portfolio Review**: \"Analyze my portfolio: 40% AAPL, 20% MSFT, 15% GOOGL, 15% AMZN, 10% TSLA — diversification, risk, and recommendations\"\n- **Asset Allocation**: \"Design an optimal portfolio for a 35-year-old with $200K, moderate risk tolerance\"\n- **Risk Assessment**: \"Calculate the Sharpe ratio, beta, and maximum drawdown for this portfolio over the last 3 years\"\n- **Rebalancing**: \"My portfolio drifted from target — recommend rebalancing trades to minimize tax impact\"\n\n### Financial Modeling\n\nBuild professional financial models:\n\n- **DCF Models**: \"Build a discounted cash flow model for Shopify with sensitivity analysis on growth and discount rate\"\n- **Startup Financial Models**: \"Create a 3-year financial projection for a B2B SaaS with $50K MRR growing 15% monthly\"\n- **LBO Models**: \"Model a leveraged buyout scenario for a $100M revenue company at 8x EBITDA\"\n- **Scenario Analysis**: \"Create a 3-scenario model (recession, baseline, boom) for a retail REIT portfolio\"\n\n### Financial Documents & Reports\n\nProfessional financial deliverables:\n\n- **Investment Memos**: \"Write an investment memo recommending a position in CrowdStrike\"\n- **Quarterly Reports**: \"Create a quarterly financial report for my small business\"\n- **Financial Statements**: \"Generate pro forma financial statements for a startup fundraise\"\n- **Tax Planning**: \"Analyze tax optimization strategies for a freelancer earning $150K with $30K in capital gains\"\n\n### Personal Finance\n\nEveryday financial planning:\n\n- **Retirement Planning**: \"How much do I need to save monthly to retire at 55 with $2M? I'm 30, saving $2K/month currently\"\n- **Mortgage Analysis**: \"Compare a 15-year vs 30-year mortgage on a $500K home with 20% down at current rates\"\n- **Debt Payoff**: \"Create a debt payoff plan: $15K student loans at 5%, $8K credit card at 22%, $25K car loan at 6%\"\n- **Budget Optimization**: \"Analyze my spending breakdown and recommend where to cut to save $1,000/month more\"\n\n---\n\n## Output Formats\n\nCellCog delivers financial analysis in multiple formats:\n\n| Format | Best For |\n|--------|----------|\n| **Interactive HTML Dashboard** | Explorable charts, drill-down analysis, live data presentation |\n| **PDF Report** | Shareable, printable investment memos and reports |\n| **XLSX Spreadsheet** | Editable financial models, projections, calculations |\n| **Markdown** | Quick analysis for integration into your docs |\n\nSpecify your preferred format in the prompt:\n- \"Deliver as an interactive HTML report with charts\"\n- \"Create a PDF investment memo\"\n- \"Build this as an editable Excel model\"\n\n---\n\n## Chat Mode for Finance\n\n| Scenario | Recommended Mode |\n|----------|------------------|\n| Quick lookups, single stock metrics, basic calculations | `\"agent\"` |\n| Deep analysis, valuation models, multi-company comparisons, investment research | `\"agent team\"` |\n| High-stakes investment decisions, M&A due diligence, institutional-grade research | `\"agent team max\"` |\n\n**Use `\"agent team\"` for most financial analysis.** Financial work demands deep reasoning, data cross-referencing, and multi-source synthesis. Agent team mode delivers the depth that serious financial analysis requires.\n\n**Use `\"agent\"` for quick financial lookups** — current stock price, simple calculations, or basic metric checks.\n\n**Use `\"agent team max\"` for high-stakes financial work** — investment decisions with significant capital at risk, M&A due diligence, regulatory filings, or boardroom-ready deliverables where the extra reasoning depth justifies the cost. Requires ≥2,000 credits.\n\n---\n\n## Example Prompts\n\n**Comprehensive stock analysis:**\n> \"Create a full investment analysis for AMD:\n> \n> 1. Business Overview — segments, revenue mix, competitive positioning\n> 2. Financial Performance — last 8 quarters revenue, margins, EPS trends\n> 3. Valuation — P/E, P/S, PEG vs peers (NVDA, INTC, QCOM)\n> 4. Growth Catalysts — AI/datacenter, gaming, embedded\n> 5. Risk Factors — competition, cyclicality, customer concentration\n> 6. Bull/Bear/Base price targets\n> \n> Interactive HTML report with comparison charts.\"\n\n**Financial model:**\n> \"Build a startup financial model:\n> \n> Business: B2B SaaS, project management tool\n> Current: $30K MRR, 200 customers, $150 ARPU\n> Growth: 12% MoM for 12 months, then 8% for next 12\n> Team: 8 people now, hiring 4 in next year\n> Expenses: $180K/month burn rate\n> \n> Create a 24-month projection showing:\n> - Revenue forecast with cohort analysis\n> - Expense breakdown and hiring plan\n> - Cash flow and runway\n> - Unit economics (CAC, LTV, payback period)\n> - Break-even analysis\n> \n> Deliver as Excel spreadsheet with charts.\"\n\n**Personal finance:**\n> \"I'm 28, earning $120K/year in San Francisco. I want to:\n> 1. Max out 401K contributions\n> 2. Build a 6-month emergency fund ($30K)\n> 3. Save for a house down payment ($100K in 5 years)\n> 4. Start investing in index funds\n> \n> Create a detailed monthly financial plan that shows how to prioritize these goals with my take-home pay after taxes. Include a timeline and visual roadmap.\"\n\n**Earnings analysis:**\n> \"Break down Tesla's most recent quarterly earnings:\n> \n> - Revenue vs estimates (beat/miss by how much?)\n> - Automotive margins — trend over last 4 quarters\n> - Energy and services segment performance\n> - Key quotes from management on guidance\n> - What analysts are saying post-earnings\n> - Bull and bear reactions\n> \n> Deliver as a concise PDF report with charts.\"\n\n---\n\n## Tips for Better Financial Analysis\n\n1. **Be specific about metrics**: \"Revenue growth\" is vague. \"YoY revenue growth for the last 8 quarters with segment breakdown\" is precise.\n\n2. **Specify time horizons**: \"Analyze AAPL\" is open-ended. \"Analyze AAPL's performance and outlook for the next 12 months\" is actionable.\n\n3. **State your purpose**: \"For an investment decision\", \"For a board presentation\", \"For personal planning\" — context shapes the analysis.\n\n4. **Include constraints**: Budget, risk tolerance, time horizon, tax situation — these matter for financial recommendations.\n\n5. **Request scenarios**: \"Include bear, base, and bull cases\" gives you a range, not just a point estimate.\n\n6. **Ask for the deliverable you need**: \"Interactive dashboard\", \"PDF memo\", \"Excel model\" — specify the format for the best result.\n\nFile v1.0.8:_meta.json\n\n{\n  \"ownerId\": \"kn7a96cj9q65e0bhmzahv790en80ffqm\",\n  \"slug\": \"stock-analysis-cellcog\",\n  \"version\": \"1.0.8\",\n  \"publishedAt\": 1775627880007\n}","readmeExcerpt":"Skill: Stock Analysis Owner: cellcog Summary: AI financial analysis and stock research powered by CellCog. Stock analysis, valuation models, portfolio optimization, earnings breakdowns, investment research, financial statements, tax planning, DCF modeling. Deliverables as interactive dashboards, PDF reports, and Excel models. Tags: latest:1.0.17 Version history: v1.0.17 | 2026-08-24T02:01:15.938Z | user Content updat","codeSnippets":[],"executableExamples":[{"language":"python","snippet":"result = client.create_chat(\n    prompt=\"[your task prompt]\",\n    notify_session_key=\"agent:main:main\",\n    task_label=\"my-task\",\n    chat_mode=\"team\",\n)"},{"language":"python","snippet":"from cellcog import CellCogClient\nclient = CellCogClient(agent_provider=\"openclaw|cursor|claude-code|codex|...\")\nresult = client.create_chat(\n    prompt=\"[your task prompt]\",\n    task_label=\"my-task\",\n    chat_mode=\"team\",\n)\nprint(result[\"message\"])"},{"language":"python","snippet":"result = client.create_chat(\n    prompt=\"[your task prompt]\",\n    notify_session_key=\"agent:main:main\",\n    task_label=\"my-task\",\n    chat_mode=\"team\",\n)"},{"language":"python","snippet":"from cellcog import CellCogClient\nclient = CellCogClient(agent_provider=\"openclaw|cursor|claude-code|codex|...\")\nresult = client.create_chat(\n    prompt=\"[your task prompt]\",\n    task_label=\"my-task\",\n    chat_mode=\"team\",\n)\nprint(result[\"message\"])"},{"language":"python","snippet":"result = client.create_chat(\n    prompt=\"[your task prompt]\",\n    notify_session_key=\"agent:main:main\",\n    task_label=\"my-task\",\n    chat_mode=\"agent\",\n)"},{"language":"python","snippet":"from cellcog import CellCogClient\nclient = CellCogClient(agent_provider=\"openclaw|cursor|claude-code|codex|...\")\nresult = client.create_chat(\n    prompt=\"[your task prompt]\",\n    task_label=\"my-task\",\n    chat_mode=\"agent\",\n)\nprint(result[\"message\"])"}],"parameters":null,"dependencies":[],"permissions":[],"extractedFiles":[{"path":"SKILL.md","content":"---\nname: stock-analysis-cellcog\ndescription: \"AI financial analysis and stock research powered by CellCog. Stock analysis, valuation models, portfolio optimization, earnings breakdowns, investment research, financial statements, tax planning, DCF modeling. Deliverables as interactive dashboards, PDF reports, and Excel models.\"\nmetadata:\n  openclaw:\n    emoji: \"💰\"\n    os: [darwin, linux, windows]\n    requires:\n      bins: [python3]\n      env: [CELLCOG_API_KEY]\nauthor: CellCog\nhomepage: https://cellcog.ai\ndependencies: [cellcog]\n---\n# Stock Analysis - Wall Street-Grade Analysis, Accessible Globally\n\n**Wall Street-grade analysis, accessible globally.** Deep financial reasoning powered by #1 on DeepResearch Bench (Apr 2026) + SOTA financial models.\n\nThe best financial analysis has always lived behind Bloomberg terminals, institutional research desks, and $500/hour consultants. CellCog brings that same depth — stock analysis, valuation models, portfolio optimization, earnings breakdowns — to anyone with a prompt. From raw tickers to boardroom-ready deliverables in one request.\n\n## How to Use\n\nFor your first CellCog task in a session, read the **cellcog** skill for the full SDK reference — file handling, chat modes, timeouts, and more.\n\n**OpenClaw (fire-and-forget):**\n```python\nresult = client.create_chat(\n    prompt=\"[your task prompt]\",\n    notify_session_key=\"agent:main:main\",\n    task_label=\"my-task\",\n    chat_mode=\"team\",\n)\n```\n\n**All agents except OpenClaw (blocks until done):**\n```python\nfrom cellcog import CellCogClient\nclient = CellCogClient(agent_provider=\"openclaw|cursor|claude-code|codex|...\")\nresult = client.create_chat(\n    prompt=\"[your task prompt]\",\n    task_label=\"my-task\",\n    chat_mode=\"team\",\n)\nprint(result[\"message\"])\n```\n\n\n---\n\n## What Financial Work You Can Do\n\n### Stock & Equity Analysis\n\nDeep dives into public companies:\n\n- **Company Analysis**: \"Analyze NVIDIA — revenue trends, margins, competitive moat, and forward guidance\"\n- **Earnings Breakdowns**: \"Break down Apple's Q4 2025 earnings — beat/miss, segment performance, management commentary\"\n- **Valuation Models**: \"Build a DCF model for Microsoft with bear, base, and bull scenarios\"\n- **Peer Comparisons**: \"Compare semiconductor stocks — NVDA, AMD, INTC, TSM — on valuation, growth, and profitability metrics\"\n- **Technical Analysis**: \"Analyze Tesla's price action — key support/resistance levels, moving averages, and volume trends\"\n\n**Example prompt:**\n> \"Create a comprehensive stock analysis for Palantir (PLTR):\n> \n> Cover:\n> - Business model and revenue breakdown (government vs commercial)\n> - Last 4 quarters earnings performance\n> - Key financial metrics (P/E, P/S, FCF margin, revenue growth)\n> - Competitive positioning vs Snowflake, Databricks, C3.ai\n> - Bull and bear thesis\n> - Valuation assessment\n> \n> Deliver as an interactive HTML report with charts.\"\n\n### Portfolio Analysis & Optimization\n\nManage and optimize investments:\n\n- **Portfolio Review**: \"Analyze my por"},{"path":"_meta.json","content":"{\n  \"ownerId\": \"kn7a96cj9q65e0bhmzahv790en80ffqm\",\n  \"slug\": \"stock-analysis-cellcog\",\n  \"version\": \"1.0.17\",\n  \"publishedAt\": 1787536875938\n}"},{"path":"skill-card.md","content":"## Description:\n\nStock Analysis helps agents use CellCog for stock research, valuation models, portfolio optimization, earnings breakdowns, investment research, financial statements, tax planning, DCF modeling, and deliverables such as dashboards, PDF reports, and Excel models.\n\nThis skill is ready for commercial/non-commercial use.\n\n## Publisher:\n\n[cellcog](https://clawhub.ai/user/cellcog)\n\n### License/Terms of Use:\n\nMIT-0\n\n## Use Case:\n\nExternal users and developers use this skill to request CellCog-powered financial research, stock analysis, portfolio analysis, financial models, and finance-focused reports from an agent.\n\n### Deployment Geography for Use:\n\nGlobal\n\n## Known Risks and Mitigations:\n\nRisk: Financial prompts, portfolio details, and related context may be sent to a third-party service.\n\nMitigation: Install only if CellCog is trusted, avoid unnecessary sensitive records, and use a restricted, rotatable CELLCOG_API_KEY.\n\nRisk: The skill provides financial, tax, legal, or investment-oriented outputs that may be incorrect or unsuitable for a user's situation.\n\nMitigation: Treat outputs as informational and require qualified human review before making financial, tax, legal, or investment decisions.\n\nRisk: Mutable install instructions can change what code or package version is installed.\n\nMitigation: Prefer a pinned, verified package or skill version before deployment.\n\n## Reference(s):\n\n- [CellCog Homepage](https://cellcog.ai)\n- [ClawHub Skill Page](https://clawhub.ai/cellcog/skills/stock-analysis-cellcog)\n\n## Skill Output:\n\n**Output Type(s):** [text, markdown, code, shell commands, configuration, guidance]\n\n**Output Format:** [Markdown guidance with Python snippets and requested financial deliverables such as HTML dashboards, PDF reports, XLSX spreadsheets, or Markdown analysis.]\n\n**Output Parameters:** [1D]\n\n**Other Properties Related to Output:** [Requires python3 and CELLCOG_API_KEY; may use the CellCog dependency and external CellCog service.]\n\n## Skill Version(s):\n\n1.0.17 (source: server release metadata)\n\n## Ethical Considerations:\n\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment."}],"languages":[],"docsSourceLabel":"CLAWHUB","editorialOverview":"AI financial analysis and stock research powered by CellCog. Stock analysis, valuation models, portfolio optimization, earnings breakdowns, investment research, financial statements, tax planning, DCF modeling. Deliverables as interactive dashboards, PDF reports, and Excel models. Skill: Stock Analysis Owner: cellcog Summary: AI financial analysis and stock research powered by CellCog. Stock analysis, valuation models, portfolio optimization, earnings breakdowns, investment research, financial statements, tax planning, DCF modeling. Deliverables as interactive dashboards, PDF reports, and Excel models. 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