{"id":"20580c54-aefb-4bee-8f8c-7cf3c9453809","entityType":"agent","slug":"clawhub-skills-1kalin-afrexai-lead-hunter","name":"afrexai-lead-hunter","canonicalUrl":"https://www.xpersona.co/agent/clawhub-skills-1kalin-afrexai-lead-hunter","canonicalPath":"/agent/clawhub-skills-1kalin-afrexai-lead-hunter","generatedAt":"2026-10-09T23:25:11.388Z","source":"CLAWHUB","claimStatus":"UNCLAIMED","verificationTier":"NONE","summary":{"evidence":{"source":"editorial-content","verified":true,"confidence":"high","updatedAt":"2026-04-15T00:45:39.800Z","emptyReason":null},"description":"Enterprise-grade B2B lead generation, enrichment, scoring, and outreach sequencing for AI agents. Find ideal prospects, enrich with verified data, score against your ICP, and generate personalized outreach — all autonomously. --- name: afrexai-lead-hunter description: \"Enterprise-grade B2B lead generation, enrichment, scoring, and outreach sequencing for AI agents. 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Find ideal prospects, enrich with verified data, score against your ICP, and generate personalized outreach — all autonomously.\"\ntags: [leads, sales, b2b, prospecting, enrichment, outreach, pipeline, crm, cold-email, icp]\nauthor: AfrexAI\nversion: 1.0.0\nlicense: MIT\n---\n\n# AfrexAI Lead Hunter Pro\n\n> Turn your AI agent into a full B2B sales development machine. Discovery → Enrichment → Scoring → Outreach → CRM. Zero manual work.\n\n---\n\n## Architecture\n\n```\nDEFINE ICP ──▶ DISCOVER ──▶ ENRICH ──▶ SCORE ──▶ SEGMENT ──▶ OUTREACH ──▶ CRM\n    │              │            │          │          │            │          │\n    ▼              ▼            ▼          ▼          ▼            ▼          ▼\n Persona      Multi-source  Email+Phone  ICP fit   Tier A/B/C  Sequences  Pipeline\n Builder      Web Research  Company Data  Intent    Campaigns   Templates  Tracking\n```\n\n---\n\n## Phase 1: Define Your Ideal Customer Profile (ICP)\n\nBefore hunting, know WHO you're hunting. Answer these:\n\n### Company-Level ICP\n```yaml\n# Copy and customize this ICP template\ncompany:\n  industries: [SaaS, fintech, legal-tech, prop-tech]\n  employee_range: [50, 500]        # sweet spot for AI adoption\n  revenue_range: [$5M, $100M]      # can afford $120K+ contracts\n  funding_stage: [Series A, Series B, Series C]\n  tech_signals:                     # tools that indicate AI readiness\n    positive: [Salesforce, HubSpot, Snowflake, AWS, Python]\n    negative: [no-website, wordpress-only]\n  geography: [US, UK, Canada, Australia]\n  pain_signals:                     # problems they're likely facing\n    - \"manual data entry\"\n    - \"compliance overhead\"\n    - \"scaling operations\"\n    - \"document processing\"\n```\n\n### Buyer Persona\n```yaml\npersona:\n  titles: [CEO, CTO, COO, VP Operations, Head of Innovation, Director of IT]\n  seniority: [C-Suite, VP, Director]\n  decision_authority: true          # can sign $50K+ without board approval\n  linkedin_activity:                # signals they're actively looking\n    - posts about AI/automation\n    - comments on digital transformation content\n    - recently changed roles (first 90 days = buying window)\n  anti-signals:                     # skip these\n    - \"consultant\" in title (not buyers)\n    - company < 10 employees (no budget)\n    - already has AI vendor (check for competitors in their stack)\n```\n\n### Scoring Weights\n```yaml\nscoring:\n  icp_company_match: 30             # how well company matches\n  icp_persona_match: 20             # right title + seniority\n  intent_signals: 25                # actively looking for solutions\n  engagement_recency: 15            # recent activity online\n  timing_bonus: 10                  # new role, funding round, hiring\n  \n  thresholds:\n    tier_a: 80                      # hot — outreach immediately\n    tier_b: 60                      # warm — nurture sequence\n    tier_c: 40                      # cool — add to newsletter\n    disqualify: below 40            # don't waste time\n```\n\n---\n\n## Phase 2: Multi-Source Discovery\n\n### Source Priority Matrix\n\n| Source | Best For | How To Search | Data Quality | Cost |\n|--------|----------|---------------|-------------|------|\n| **Web Search** | Any industry | `\"[industry] companies\" site:linkedin.com/company` | High | Free |\n| **GitHub** | Dev tools, tech companies | Search repos, org pages, contributor profiles | High | Free |\n| **Product Hunt** | Startups, SaaS | Browse launches, upvoters (they're buyers too) | Medium | Free |\n| **Industry Lists** | Targeted verticals | \"Top 50 [industry] companies 2026\", Clutch, G2 | High | Free |\n| **Job Boards** | Hiring = growing = buying | `\"AI\" OR \"automation\" site:lever.co OR site:greenhouse.io` | High | Free |\n| **Crunchbase** | Funded startups | Recently funded companies in target verticals | High | Freemium |\n| **Conference Speakers** | Active industry leaders | Speaker lists from industry events | Very High | Free |\n| **Podcast Guests** | Thought leaders with budget | Search \"[industry] podcast\" transcripts | High | Free |\n\n### Discovery Search Templates\n\n**Find companies by pain signal:**\n```\n\"[industry]\" \"manual process\" OR \"time-consuming\" OR \"looking for solutions\" site:linkedin.com\n```\n\n**Find companies by hiring signal (they're growing = they're buying):**\n```\n\"[company type]\" \"hiring\" \"AI\" OR \"automation\" OR \"data\" site:linkedin.com/jobs\n```\n\n**Find recently funded companies (flush with cash):**\n```\n\"[industry]\" \"raises\" OR \"Series A\" OR \"funding\" OR \"investment\" 2026\n```\n\n**Find companies using competitor tools (ripe for switching):**\n```\n\"[competitor tool]\" \"alternative\" OR \"switching from\" OR \"replaced\"\n```\n\n**Find decision makers directly:**\n```\n\"[title]\" \"[industry]\" \"[city/region]\" site:linkedin.com/in\n```\n\n### Discovery Workflow\n\n```\nFOR each search query:\n  1. Run web_search with the query\n  2. Extract company names + URLs from results\n  3. Deduplicate against existing leads\n  4. For each NEW company:\n     a. Visit company website → extract: industry, size estimate, tech signals\n     b. Search \"[company name] CEO\" OR \"[company name] founder\" → get decision maker\n     c. Search \"[company name] funding\" → get financial signals\n     d. Create lead record (see schema below)\n  5. Rate limit: 2-3 second delay between searches\n```\n\n---\n\n## Phase 3: Enrichment Engine\n\nFor each discovered lead, enrich with verified data:\n\n### Company Enrichment Checklist\n- [ ] **Website** — Load homepage, extract value prop, tech stack (check `<meta>` tags, JS frameworks)\n- [ ] **Employee Count** — LinkedIn company page, Crunchbase, or website \"About\" page\n- [ ] **Revenue Estimate** — Funding amount × 3-5x multiplier, or industry benchmarks\n- [ ] **Tech Stack** — Check BuiltWith, Wappalyzer data, or job postings for tech mentions\n- [ ] **Recent News** — Last 90 days: funding, launches, executive changes, partnerships\n- [ ] **Pain Indicators** — Job postings mentioning problems you solve, blog posts about challenges\n- [ ] **Competitor Usage** — Do they use a competitor? Which one? (Check G2 reviews, case studies)\n\n### Contact Enrichment Checklist\n- [ ] **Full Name** — First + Last from LinkedIn or company page\n- [ ] **Title** — Current role (verify it matches your buyer persona)\n- [ ] **Email Pattern** — Determine company pattern: first@, first.last@, firstlast@, f.last@\n- [ ] **Email Verification** — Test pattern with known format, check MX records\n- [ ] **LinkedIn URL** — Direct profile link\n- [ ] **Recent Activity** — What have they posted/shared in last 30 days?\n- [ ] **Mutual Connections** — Anyone in your network connected to them?\n- [ ] **Content Interests** — What topics do they engage with? (Use for personalization)\n\n### Email Pattern Detection\n```\nCommon patterns (test in order of likelihood):\n1. first.last@company.com     (most common, ~40%)\n2. first@company.com          (startups, ~25%)\n3. firstlast@company.com      (~15%)\n4. flast@company.com           (~10%)\n5. first_last@company.com     (~5%)\n6. last.first@company.com     (~3%)\n7. first.l@company.com        (~2%)\n\nVerification approach:\n- Check if company has public team page with email format\n- Look for email in GitHub commits from company domain\n- Check email format on Hunter.io or similar (if available)\n- Search \"[person name] email [company]\" \n- Check their personal website/blog for contact\n```\n\n---\n\n## Phase 4: Lead Scoring Algorithm\n\nScore each lead 0-100 using this rubric:\n\n### Company Score (0-30 points)\n\n| Signal | Points | How to Check |\n|--------|--------|-------------|\n| Industry matches ICP exactly | +10 | Compare to ICP config |\n| Employee count in sweet spot | +5 | LinkedIn/website |\n| Revenue in target range | +5 | Crunchbase/estimate |\n| Located in target geography | +3 | Website/LinkedIn |\n| Uses compatible tech stack | +4 | Job posts, BuiltWith |\n| No competitor currently | +3 | Research, case studies |\n\n### Persona Score (0-20 points)\n\n| Signal | Points | How to Check |\n|--------|--------|-------------|\n| Title matches buyer persona | +8 | LinkedIn |\n| C-Suite or VP level | +5 | LinkedIn |\n| Has decision authority | +4 | Title + company size |\n| Active on LinkedIn (posts monthly) | +3 | LinkedIn activity |\n\n### Intent Score (0-25 points)\n\n| Signal | Points | How to Check |\n|--------|--------|-------------|\n| Recently posted about relevant pain | +8 | LinkedIn/Twitter |\n| Company hiring for roles you'd replace | +7 | Job boards |\n| Attended relevant industry event | +5 | Conference lists |\n| Downloaded competitor content | +3 | Hard to verify, skip if unknown |\n| Searched for solution keywords | +2 | Hard to verify, skip if unknown |\n\n### Timing Score (0-15 points)\n\n| Signal | Points | How to Check |\n|--------|--------|-------------|\n| New in role (< 90 days) | +5 | LinkedIn start date |\n| Company just raised funding | +4 | Crunchbase/news |\n| End of quarter (budget flush) | +3 | Calendar |\n| Company growing fast (hiring surge) | +3 | Job postings count |\n\n### Engagement Score (0-10 points)\n\n| Signal | Points | How to Check |\n|--------|--------|-------------|\n| Opened previous email | +4 | Email tracking |\n| Visited your website | +3 | Analytics |\n| Connected on LinkedIn | +2 | LinkedIn |\n| Referred by someone | +1 | CRM notes |\n\n---\n\n## Phase 5: Segmentation & Campaign Assignment\n\n### Tier A (Score 80-100) — HOT LEADS\n```\nAction: Immediate personalized outreach\nSequence: 5-touch hyper-personalized campaign\nTimeline: Contact within 24 hours\nChannel: Email → LinkedIn → Phone (if available)\nTemplate: \"CEO-to-CEO\" or \"Specific Pain\" (see below)\n```\n\n### Tier B (Score 60-79) — WARM LEADS\n```\nAction: Nurture sequence\nSequence: 7-touch value-first campaign  \nTimeline: Start within 48 hours\nChannel: Email → LinkedIn\nTemplate: \"Value Insight\" or \"Case Study\" (see below)\n```\n\n### Tier C (Score 40-59) — COOL LEADS\n```\nAction: Add to newsletter + long-term nurture\nSequence: Monthly value content\nTimeline: Bi-weekly touchpoints\nChannel: Email only\nTemplate: \"Industry Report\" or \"Educational\" (see below)\n```\n\n---\n\n## Phase 6: Outreach Sequence Templates\n\n### Template 1: The Specific Pain (Tier A)\n\n**Email 1 — Day 0 (The Hook)**\n```\nSubject: [specific pain point] at [Company]?\n\nHi [First Name],\n\nNoticed [Company] is [specific observation — hiring for X role / posted about Y challenge / using Z tool].\n\nThat usually means [pain point they're likely feeling].\n\nWe built [solution] that [specific result with number]. [Client name] cut their [metric] by [X%] in [timeframe].\n\nWorth a 15-min call to see if it fits [Company]?\n\n[Your name]\n```\n\n**Email 2 — Day 3 (The Proof)**\n```\nSubject: Re: [original subject]\n\n[First Name] — quick follow-up.\n\nHere's exactly what we did for [similar company]: [1-sentence case study with specific numbers].\n\n[Link to case study or calculator]\n\nHappy to walk through how this maps to [Company].\n\n[Your name]\n```\n\n**Email 3 — Day 7 (The Angle)**\n```\nSubject: [industry trend] + [Company]\n\n[First Name],\n\n[Industry trend or stat that's relevant]. Companies like [Company] are [what smart companies are doing about it].\n\nWe help [type of company] [specific outcome]. Takes about [timeframe] to see results.\n\nOpen to a quick chat this week?\n\n[Your name]\n```\n\n**Email 4 — Day 14 (The Breakup)**\n```\nSubject: Should I close your file?\n\n[First Name],\n\nI've reached out a few times — totally understand if the timing isn't right.\n\nIf [pain point] becomes a priority, here's a [free resource] that might help: [link]\n\nEither way, I'll stop filling your inbox. Just reply \"yes\" if you'd like to chat sometime.\n\n[Your name]\n```\n\n### Template 2: The Value-First (Tier B)\n\n**Email 1 — Lead with insight, not a pitch**\n```\nSubject: [number] [industry] companies are doing [thing] wrong\n\nHi [First Name],\n\nWe analyzed [X] companies in [industry] and found that [surprising insight].\n\nThe ones getting it right are [what top performers do differently].\n\nPut together a quick breakdown: [link to free resource/calculator]\n\nThought it'd be useful given what [Company] is building.\n\n[Your name]\n```\n\n### Template 3: The LinkedIn Warm-Up\n\n**Step 1:** View their profile (creates notification)\n**Step 2 (Day 2):** Like/comment on their recent post (genuine, not generic)\n**Step 3 (Day 4):** Send connection request with note:\n```\nHi [Name] — been following [Company]'s work in [space]. \nParticularly liked your take on [specific post topic]. \nWould love to connect.\n```\n**Step 4 (Day 7, after accepted):** Send value message (NOT a pitch):\n```\n[Name] — saw you mentioned [challenge] in your recent post. \nWe put together [free resource] that addresses exactly that. \nThought you might find it useful: [link]\n```\n\n---\n\n## Phase 7: CRM & Pipeline Management\n\n### Lead Record Schema\n```json\n{\n  \"id\": \"lead-001\",\n  \"created\": \"2026-02-13\",\n  \"source\": \"web-search\",\n  \n  \"company\": {\n    \"name\": \"Acme Corp\",\n    \"website\": \"https://acme.com\",\n    \"industry\": \"SaaS\",\n    \"employees\": 150,\n    \"revenue_est\": \"$20M\",\n    \"funding\": \"Series B — $15M (2025)\",\n    \"tech_stack\": [\"Salesforce\", \"AWS\", \"React\"],\n    \"location\": \"San Francisco, CA\"\n  },\n  \n  \"contact\": {\n    \"first_name\": \"Jane\",\n    \"last_name\": \"Smith\",\n    \"title\": \"VP of Operations\",\n    \"email\": \"jane.smith@acme.com\",\n    \"email_verified\": false,\n    \"linkedin\": \"https://linkedin.com/in/janesmith\",\n    \"phone\": null\n  },\n  \n  \"scoring\": {\n    \"company_score\": 25,\n    \"persona_score\": 18,\n    \"intent_score\": 15,\n    \"timing_score\": 8,\n    \"engagement_score\": 0,\n    \"total\": 66,\n    \"tier\": \"B\"\n  },\n  \n  \"enrichment\": {\n    \"pain_signals\": [\"hiring 3 data analysts\", \"blog about manual reporting\"],\n    \"recent_news\": [\"Raised Series B in Jan 2026\"],\n    \"competitor_usage\": \"None detected\",\n    \"content_interests\": [\"data automation\", \"operational efficiency\"]\n  },\n  \n  \"outreach\": {\n    \"status\": \"not_started\",\n    \"sequence\": \"value-first\",\n    \"emails_sent\": 0,\n    \"last_contacted\": null,\n    \"next_action\": \"2026-02-14\",\n    \"replies\": [],\n    \"notes\": \"\"\n  },\n  \n  \"pipeline\": {\n    \"stage\": \"prospect\",\n    \"deal_value\": null,\n    \"probability\": 0,\n    \"next_step\": \"Initial outreach\"\n  }\n}\n```\n\n### Pipeline Stages\n```\nPROSPECT → CONTACTED → REPLIED → MEETING_BOOKED → QUALIFIED → PROPOSAL → NEGOTIATION → CLOSED_WON / CLOSED_LOST\n```\n\n### Tracking Metrics\nTrack these weekly to optimize your machine:\n- **Discovery rate**: leads found per search session\n- **Enrichment completeness**: % of fields filled per lead\n- **Score distribution**: what % are Tier A vs B vs C?\n- **Response rate**: replies / emails sent (target: 5-15%)\n- **Meeting rate**: meetings / replies (target: 30-50%)\n- **Conversion rate**: deals / meetings (target: 20-30%)\n- **Pipeline velocity**: days from discovery → closed deal\n\n---\n\n## Phase 8: Automation & Scheduling\n\n### Daily Autopilot Routine\n```\nMORNING (agent runs autonomously):\n  1. Run 3-5 discovery searches (rotate queries)\n  2. Enrich any un-enriched leads from yesterday\n  3. Score new leads\n  4. Send Day-N emails for active sequences\n  5. Check for replies → flag for human review\n  6. Update pipeline stages\n  7. Report: \"Found X leads, sent Y emails, Z replies\"\n\nWEEKLY:\n  1. Review Tier C leads — any moved to B/A?\n  2. Clean dead leads (no response after full sequence)\n  3. Analyze response rates by template — A/B test\n  4. Refresh ICP based on closed deals\n  5. Add new search queries based on wins\n```\n\n### Agent Integration\n```\n# In your agent's heartbeat or cron:\n1. Load ICP config\n2. Run discovery for 1 search query\n3. Enrich top 5 new leads\n4. Score all unscored leads\n5. Queue outreach for Tier A leads\n6. Log results to daily brief\n```\n\n---\n\n## Output Formats\n\n### CSV Export\n```csv\ncompany,contact,title,email,linkedin,score,tier,industry,employees,pain_signal\nAcme Corp,Jane Smith,VP Ops,jane@acme.com,linkedin.com/in/jane,66,B,SaaS,150,hiring analysts\n```\n\n### Weekly Report Template\n```markdown\n# Lead Hunter Weekly Report — Week of [DATE]\n\n## Pipeline Summary\n- Total leads in system: [N]\n- New leads this week: [N]  \n- Tier A: [N] | Tier B: [N] | Tier C: [N]\n\n## Outreach Performance\n- Emails sent: [N]\n- Reply rate: [X%]\n- Meetings booked: [N]\n- Pipeline value added: $[X]\n\n## Top Leads This Week\n1. [Company] — [Contact] — Score: [X] — [Why they're hot]\n2. [Company] — [Contact] — Score: [X] — [Why they're hot]\n3. [Company] — [Contact] — Score: [X] — [Why they're hot]\n\n## Insights\n- Best performing search query: [query]\n- Best performing email template: [template]\n- Recommendation: [action to take]\n```\n\n---\n\n## Pro Tips\n\n1. **The 90-Day Window**: New executives are 10x more likely to buy in their first 90 days. Prioritize \"new role\" signals.\n2. **Hiring = Buying**: If a company is hiring for the role your product replaces, they have budget AND pain. These are your hottest leads.\n3. **Competitor's Customers**: Search for reviews/complaints about competitors. Unhappy customers switch fastest.\n4. **Conference Lists**: Speaker and attendee lists from industry events are gold. These people are actively engaged in the space.\n5. **The \"Reply to Anything\" Rule**: Any reply (even \"not interested\") is valuable. It confirms the email works and the person exists. Log it.\n6. **Personalization > Volume**: 20 hyper-personalized emails outperform 200 generic ones. Always reference something specific about the prospect.\n7. **Multi-Thread**: Don't rely on one contact per company. Find 2-3 decision-makers and approach from different angles.\n8. **Timing Matters**: Tuesday-Thursday, 8-10 AM local time gets the best open rates. Avoid Mondays and Fridays.\n\n---\n\n*Built by [AfrexAI](https://afrexai-cto.github.io/context-packs/) — AI agents that actually sell.*\n","readmeExcerpt":"--- name: afrexai-lead-hunter description: \"Enterprise-grade B2B lead generation, enrichment, scoring, and outreach sequencing for AI agents. Find ideal prospects, enrich with verified data, score against your ICP, and generate personalized outreach — all autonomously.\" tags: [leads, sales, b2b, prospecting, enrichment, outreach, pipeline, crm, cold-email, icp] author: AfrexAI version: 1.0.0 license: MIT --- AfrexAI ","codeSnippets":[],"executableExamples":[{"language":"text","snippet":"DEFINE ICP ──▶ DISCOVER ──▶ ENRICH ──▶ SCORE ──▶ SEGMENT ──▶ OUTREACH ──▶ CRM\n    │              │            │          │          │            │          │\n    ▼              ▼            ▼          ▼          ▼            ▼          ▼\n Persona      Multi-source  Email+Phone  ICP fit   Tier A/B/C  Sequences  Pipeline\n Builder      Web Research  Company Data  Intent    Campaigns   Templates  Tracking"},{"language":"yaml","snippet":"# Copy and customize this ICP template\ncompany:\n  industries: [SaaS, fintech, legal-tech, prop-tech]\n  employee_range: [50, 500]        # sweet spot for AI adoption\n  revenue_range: [$5M, $100M]      # can afford $120K+ contracts\n  funding_stage: [Series A, Series B, Series C]\n  tech_signals:                     # tools that indicate AI readiness\n    positive: [Salesforce, HubSpot, Snowflake, AWS, Python]\n    negative: [no-website, wordpress-only]\n  geography: [US, UK, Canada, Australia]\n  pain_signals:                     # problems they're likely facing\n    - \"manual data entry\"\n    - \"compliance overhead\"\n    - \"scaling operations\"\n    - \"document processing\""},{"language":"yaml","snippet":"persona:\n  titles: [CEO, CTO, COO, VP Operations, Head of Innovation, Director of IT]\n  seniority: [C-Suite, VP, Director]\n  decision_authority: true          # can sign $50K+ without board approval\n  linkedin_activity:                # signals they're actively looking\n    - posts about AI/automation\n    - comments on digital transformation content\n    - recently changed roles (first 90 days = buying window)\n  anti-signals:                     # skip these\n    - \"consultant\" in title (not buyers)\n    - company < 10 employees (no budget)\n    - already has AI vendor (check for competitors in their stack)"},{"language":"yaml","snippet":"scoring:\n  icp_company_match: 30             # how well company matches\n  icp_persona_match: 20             # right title + seniority\n  intent_signals: 25                # actively looking for solutions\n  engagement_recency: 15            # recent activity online\n  timing_bonus: 10                  # new role, funding round, hiring\n  \n  thresholds:\n    tier_a: 80                      # hot — outreach immediately\n    tier_b: 60                      # warm — nurture sequence\n    tier_c: 40                      # cool — add to newsletter\n    disqualify: below 40            # don't waste time"},{"language":"text","snippet":"\"[industry]\" \"manual process\" OR \"time-consuming\" OR \"looking for solutions\" site:linkedin.com"},{"language":"text","snippet":"\"[company type]\" \"hiring\" \"AI\" OR \"automation\" OR \"data\" site:linkedin.com/jobs"}],"parameters":{},"dependencies":[],"permissions":[],"extractedFiles":[],"languages":["typescript"],"docsSourceLabel":"CLAWHUB","editorialOverview":"Enterprise-grade B2B lead generation, enrichment, scoring, and outreach sequencing for AI agents. Find ideal prospects, enrich with verified data, score against your ICP, and generate personalized outreach — all autonomously. --- name: afrexai-lead-hunter description: \"Enterprise-grade B2B lead generation, enrichment, scoring, and outreach sequencing for AI agents. Find ideal prospects, enrich with verified data, score against your ICP, and generate personalized outreach — all autonomously.\" tags: [leads, sales, b2b, prospecting, enrichment, outreach, pipeline, crm, cold-email, icp] author: AfrexAI version: 1.0.0 license: MIT --- AfrexAI","editorialQuality":{"score":100,"threshold":65,"status":"ready","wordCount":395,"uniquenessScore":63,"reasons":[]}},"media":{"evidence":{"source":"no-media","verified":false,"confidence":"low","updatedAt":"2026-04-15T00:45:39.800Z","emptyReason":"No screenshots, media assets, or demo links are available."},"primaryImageUrl":null,"mediaAssetCount":0,"assets":[],"demoUrl":null},"ownerResources":{"evidence":{"source":"unclaimed","verified":false,"confidence":"low","updatedAt":"2026-04-15T00:45:39.800Z","emptyReason":"This page has not been claimed by the agent owner."},"hasCustomPage":false,"customPageUpdatedAt":null,"customLinks":[],"structuredLinks":{"docsUrl":null,"demoUrl":null,"supportUrl":null,"pricingUrl":null,"statusUrl":null},"customPage":null},"relatedAgents":{"evidence":{"source":"protocol-neighbors","verified":false,"confidence":"medium","updatedAt":"2026-10-09T23:25:11.388Z","emptyReason":null},"items":[{"id":"8ebccd8e-3863-4187-8355-c3f14e1f9edf","entityType":"agent","canonicalPath":"/agent/iofficeai-aionui","slug":"iofficeai-aionui","name":"AionUi","description":"Free, local, open-source 24/7 Cowork app and OpenClaw for Gemini CLI, Claude Code, Codex, OpenCode, Qwen Code, Goose CLI, Auggie, and more | 🌟 Star if you like it!","url":"https://github.com/iOfficeAI/AionUi","homepage":"https://www.aionui.com","source":"GITHUB_REPOS","protocols":["MCP","OPENCLAW"],"capabilities":[],"safetyScore":100,"overallRank":70,"updatedAt":"2026-10-09T19:11:12.944Z","createdAt":"2026-02-25T03:38:16.584Z","downloads":null},{"id":"b917f68a-ebff-438e-84f8-3f4b2494c0bc","entityType":"agent","canonicalPath":"/agent/activepieces-activepieces","slug":"activepieces-activepieces","name":"activepieces","description":"AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents","url":"https://github.com/activepieces/activepieces","homepage":"https://www.activepieces.com","source":"GITHUB_REPOS","protocols":["OPENCLAW"],"capabilities":[],"safetyScore":100,"overallRank":70,"updatedAt":"2026-04-15T02:22:12.426Z","createdAt":"2026-02-25T03:38:12.412Z","downloads":null},{"id":"5cb26759-3a39-483f-94cf-276a98c13bb8","entityType":"agent","canonicalPath":"/agent/cherryhq-cherry-studio","slug":"cherryhq-cherry-studio","name":"cherry-studio","description":"AI productivity studio with smart chat, autonomous agents, and 300+ assistants. 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