{"id":"fd3bcb59-dc85-46b4-8116-629edca5d96b","entityType":"agent","slug":"clawhub-skills-1kalin-afrexai-revenue-forecasting","name":"afrexai-revenue-forecasting","canonicalUrl":"https://www.xpersona.co/agent/clawhub-skills-1kalin-afrexai-revenue-forecasting","canonicalPath":"/agent/clawhub-skills-1kalin-afrexai-revenue-forecasting","generatedAt":"2026-10-09T23:47:40.825Z","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":"Revenue Forecasting Engine Revenue Forecasting Engine Build accurate, data-driven revenue forecasts your board and investors actually trust. What This Does Generates a complete revenue forecasting model covering: 1. **Pipeline-Weighted Forecast** — Apply stage-specific close rates to your current pipeline 2. **Cohort Analysis** — Track revenue by customer cohort with expansion/contraction/churn 3. **Scenario Modeling** — Bear/base/bull project","descriptionLabel":"Technical summary","evidenceSummary":"Capability contract not published. No trust telemetry is available yet. Last updated 4/15/2026.","installCommand":"clawhub skill install skills:1kalin:afrexai-revenue-forecasting","sourceUrl":"https://github.com/openclaw/skills/tree/main/skills/1kalin/afrexai-revenue-forecasting","homepage":null,"primaryLinks":[{"label":"View on ClawHub","url":"https://github.com/openclaw/skills/tree/main/skills/1kalin/afrexai-revenue-forecasting","kind":"source"}],"safetyScore":84,"overallRank":62,"popularityScore":50,"trustScore":null,"claimedByName":null,"isOwner":false,"seoDescription":"Revenue Forecasting Engine Revenue Forecasting Engine Build accurate, data-driven revenue forecasts your board and investors actually trust. What This Does Gene"},"coverage":{"evidence":{"source":"public-profile","verified":false,"confidence":"medium","updatedAt":"2026-04-15T00:45:39.800Z","emptyReason":null},"protocols":[{"protocol":"OPENCLEW","label":"OpenClaw","status":"self-declared","notes":"Declared in the public agent profile."}],"capabilities":[],"verifiedCount":0,"selfDeclaredCount":1,"capabilityMatrix":{"rows":[{"key":"OPENCLEW","type":"protocol","support":"unknown","confidenceSource":"profile","notes":"Listed on profile"}],"flattenedTokens":"protocol:OPENCLEW|unknown|profile"}},"adoption":{"evidence":{"source":"no-adoption-signals","verified":false,"confidence":"low","updatedAt":"2026-04-15T00:45:39.800Z","emptyReason":"No source adoption metrics were available."},"stars":null,"forks":null,"downloads":null,"packageName":null,"latestVersion":null,"tractionLabel":null},"release":{"evidence":{"source":"agent-index","verified":false,"confidence":"medium","updatedAt":"2026-02-25T06:18:02.236Z","emptyReason":null},"lastUpdatedAt":"2026-04-15T00:45:39.800Z","lastCrawledAt":"2026-02-25T06:18:02.236Z","lastIndexedAt":null,"nextCrawlAt":"2026-02-26T06:18:02.236Z","lastVerifiedAt":null,"highlights":[]},"execution":{"evidence":{"source":"CLAWHUB","verified":false,"confidence":"low","updatedAt":null,"emptyReason":"No published capability contract is available yet."},"installCommand":"clawhub skill install skills:1kalin:afrexai-revenue-forecasting","setupComplexity":"low","setupSteps":["Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.","Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data."],"contract":{"contractStatus":"missing","authModes":[],"requires":[],"forbidden":[],"supportsMcp":false,"supportsA2a":false,"supportsStreaming":false,"inputSchemaRef":null,"outputSchemaRef":null,"dataRegion":null,"contractUpdatedAt":null,"sourceUpdatedAt":null,"freshnessSeconds":null},"invocationGuide":{"preferredApi":{"snapshotUrl":"https://www.xpersona.co/api/v1/agents/clawhub-skills-1kalin-afrexai-revenue-forecasting/snapshot","contractUrl":"https://www.xpersona.co/api/v1/agents/clawhub-skills-1kalin-afrexai-revenue-forecasting/contract","trustUrl":"https://www.xpersona.co/api/v1/agents/clawhub-skills-1kalin-afrexai-revenue-forecasting/trust"},"curlExamples":["curl -s \"https://www.xpersona.co/api/v1/agents/clawhub-skills-1kalin-afrexai-revenue-forecasting/snapshot\"","curl -s \"https://www.xpersona.co/api/v1/agents/clawhub-skills-1kalin-afrexai-revenue-forecasting/contract\"","curl -s \"https://www.xpersona.co/api/v1/agents/clawhub-skills-1kalin-afrexai-revenue-forecasting/trust\""],"jsonRequestTemplate":{"query":"summarize this repo","constraints":{"maxLatencyMs":2000,"protocolPreference":["OPENCLEW"]}},"jsonResponseTemplate":{"ok":true,"result":{"summary":"...","confidence":0.9},"meta":{"source":"CLAWHUB","generatedAt":"2026-10-09T23:47:40.825Z"}},"retryPolicy":{"maxAttempts":3,"backoffMs":[500,1500,3500],"retryableConditions":["HTTP_429","HTTP_503","NETWORK_TIMEOUT"]}},"endpoints":{"dossierUrl":"https://www.xpersona.co/api/v1/agents/clawhub-skills-1kalin-afrexai-revenue-forecasting/dossier","snapshotUrl":"https://www.xpersona.co/api/v1/agents/clawhub-skills-1kalin-afrexai-revenue-forecasting/snapshot","contractUrl":"https://www.xpersona.co/api/v1/agents/clawhub-skills-1kalin-afrexai-revenue-forecasting/contract","trustUrl":"https://www.xpersona.co/api/v1/agents/clawhub-skills-1kalin-afrexai-revenue-forecasting/trust"}},"reliability":{"evidence":{"source":"runtime-metrics","verified":false,"confidence":"low","updatedAt":null,"emptyReason":"No trust, reliability, or runtime telemetry is available."},"trust":{"status":"unavailable","handshakeStatus":"UNKNOWN","verificationFreshnessHours":null,"reputationScore":null,"p95LatencyMs":null,"successRate30d":null,"fallbackRate":null,"attempts30d":null,"trustUpdatedAt":null,"trustConfidence":"unknown","sourceUpdatedAt":null,"freshnessSeconds":null},"decisionGuardrails":{"doNotUseIf":["Contract metadata is missing or unavailable for deterministic execution."],"safeUseWhen":[],"riskFlags":["missing_or_unavailable_contract","trust_data_unavailable","schema_references_missing"],"operationalConfidence":"low"},"executionMetrics":{"observedLatencyMsP50":null,"observedLatencyMsP95":null,"estimatedCostUsd":null,"uptime30d":null,"rateLimitRpm":null,"rateLimitBurst":null,"lastVerifiedAt":null,"verificationSource":null},"runtimeMetrics":{"successRate":null,"avgLatencyMs":null,"avgCostUsd":null,"hallucinationRate":null,"retryRate":null,"disputeRate":null,"p50Latency":null,"p95Latency":null,"lastUpdated":null}},"benchmarks":{"evidence":{"source":"no-benchmark-data","verified":false,"confidence":"low","updatedAt":null,"emptyReason":"No benchmark suites or observed failure patterns are available."},"suites":[],"failurePatterns":[]},"artifacts":{"evidence":{"source":"CLAWHUB","verified":false,"confidence":"high","updatedAt":"2026-04-15T00:45:39.800Z","emptyReason":null},"readme":"# Revenue Forecasting Engine\n\nBuild accurate, data-driven revenue forecasts your board and investors actually trust.\n\n## What This Does\n\nGenerates a complete revenue forecasting model covering:\n\n1. **Pipeline-Weighted Forecast** — Apply stage-specific close rates to your current pipeline\n2. **Cohort Analysis** — Track revenue by customer cohort with expansion/contraction/churn\n3. **Scenario Modeling** — Bear/base/bull projections with probability weighting\n4. **Seasonality Adjustments** — Monthly coefficients based on your historical patterns\n5. **Leading Indicators** — Track signals that predict revenue 60-90 days out\n\n## Instructions\n\nWhen the user asks for a revenue forecast, follow this framework:\n\n### Step 1: Gather Inputs\nAsk for (or use available data):\n- Current MRR/ARR\n- Pipeline by stage with deal values\n- Historical close rates by stage\n- Average sales cycle length\n- Net revenue retention rate\n- Expansion revenue %\n\n### Step 2: Build the Pipeline Forecast\n\n**Stage-Weighted Model:**\n\n| Stage | Probability | Weighted Value |\n|-------|------------|----------------|\n| Discovery | 10% | Deal × 0.10 |\n| Demo/Eval | 25% | Deal × 0.25 |\n| Proposal Sent | 50% | Deal × 0.50 |\n| Negotiation | 75% | Deal × 0.75 |\n| Verbal Commit | 90% | Deal × 0.90 |\n| Closed Won | 100% | Deal × 1.00 |\n\n**Adjustment factors:**\n- Deal age penalty: -5% per month past avg cycle\n- Champion risk: -20% if no identified champion\n- Budget confirmed: +10% if budget is allocated\n- Competitive deal: -15% if competitor identified\n\n### Step 3: Cohort Revenue Model\n\nTrack each monthly cohort:\n```\nMonth 0: New MRR from cohort\nMonth 1: Retained MRR × (1 - monthly churn rate)\nMonth 3: Add expansion revenue (avg 2-5% monthly for healthy SaaS)\nMonth 6: Steady-state retention rate applies\nMonth 12: Mature cohort — use net revenue retention\n```\n\n**Benchmarks by company stage:**\n| Metric | Seed | Series A | Series B+ |\n|--------|------|----------|-----------|\n| Gross Churn | 3-5%/mo | 2-3%/mo | 1-2%/mo |\n| Net Retention | 90-100% | 100-110% | 110-130% |\n| Expansion % | 5-10% | 10-20% | 20-40% |\n| CAC Payback | 18-24 mo | 12-18 mo | 6-12 mo |\n\n### Step 4: Scenario Analysis\n\n**Bear Case (20% probability):**\n- Pipeline closes at 60% of weighted value\n- Churn increases 50%\n- No expansion revenue\n- 1 key deal slips each quarter\n\n**Base Case (60% probability):**\n- Pipeline closes at weighted value\n- Current retention rates hold\n- Historical expansion rate\n- Normal seasonality\n\n**Bull Case (20% probability):**\n- Pipeline closes at 120% of weighted value\n- Retention improves 10%\n- Expansion accelerates 25%\n- 1 surprise large deal per quarter\n\n**Expected Value = (Bear × 0.2) + (Base × 0.6) + (Bull × 0.2)**\n\n### Step 5: Seasonality Coefficients\n\nApply monthly adjustment factors:\n| Month | B2B SaaS | Ecommerce | Professional Services |\n|-------|----------|-----------|---------------------|\n| Jan | 0.85 | 0.70 | 0.90 |\n| Feb | 0.90 | 0.75 | 0.95 |\n| Mar | 1.05 | 0.85 | 1.10 |\n| Apr | 1.00 | 0.90 | 1.00 |\n| May | 0.95 | 0.90 | 0.95 |\n| Jun | 1.10 | 0.95 | 1.05 |\n| Jul | 0.85 | 0.85 | 0.85 |\n| Aug | 0.80 | 0.90 | 0.80 |\n| Sep | 1.10 | 1.00 | 1.10 |\n| Oct | 1.05 | 1.05 | 1.05 |\n| Nov | 1.15 | 1.40 | 1.10 |\n| Dec | 1.20 | 1.75 | 1.15 |\n\n### Step 6: Leading Indicators Dashboard\n\nTrack these weekly — they predict revenue 60-90 days out:\n\n| Indicator | Weight | Signal |\n|-----------|--------|--------|\n| Qualified pipeline created | 25% | New opps entering Stage 2+ |\n| Demo-to-proposal rate | 20% | Conversion velocity |\n| Average deal size trend | 15% | Moving up or down? |\n| Sales cycle length | 15% | Getting longer = red flag |\n| Inbound lead volume | 10% | Marketing effectiveness |\n| Website trial signups | 10% | Self-serve demand |\n| Customer NPS/CSAT | 5% | Retention predictor |\n\n### Step 7: Output Format\n\nPresent the forecast as:\n\n```\nREVENUE FORECAST — [Period]\n================================\nCurrent ARR: $X\nPipeline (Weighted): $X\nExpected New ARR: $X\n\n12-Month Projection:\n  Bear:  $X (20%)\n  Base:  $X (60%)\n  Bull:  $X (20%)\n  Expected: $X\n\nKey Risks:\n  1. [Risk] — [Mitigation]\n  2. [Risk] — [Mitigation]\n\nLeading Indicators:\n  🟢 [Healthy metric]\n  🟡 [Watch metric]\n  🔴 [Concerning metric]\n\nNext Month Actions:\n  1. [Specific action]\n  2. [Specific action]\n```\n\n## Red Flags to Call Out\n\n- Pipeline coverage < 3x target = high risk\n- >40% of forecast from 1-2 deals = concentration risk\n- Average deal age exceeding 1.5x normal cycle = stalling\n- Declining demo-to-close rate = product-market fit erosion\n- Rising CAC payback period = unit economics degrading\n\n## Revenue Recognition Notes\n\n- SaaS: Recognize ratably over contract term\n- Services: Recognize on delivery/milestones\n- Usage-based: Recognize on consumption\n- Annual prepay: Deferred revenue, recognize monthly\n\n---\n\n*Built by [AfrexAI](https://afrexai-cto.github.io/context-packs/) — AI context packs for business operators who ship.*\n\n**Get the full toolkit:**\n- [AI Revenue Leak Calculator](https://afrexai-cto.github.io/ai-revenue-calculator/) — Find where you're losing money\n- [Context Packs](https://afrexai-cto.github.io/context-packs/) — Industry-specific AI agent configs ($47/pack)\n- [Agent Setup Wizard](https://afrexai-cto.github.io/agent-setup/) — Deploy your first AI agent in 15 minutes\n\n**Bundles:** Playbook $27 | Pick 3 for $97 | All 10 for $197 | Everything Bundle $247\n","readmeExcerpt":"Revenue Forecasting Engine Build accurate, data-driven revenue forecasts your board and investors actually trust. What This Does Generates a complete revenue forecasting model covering: 1. **Pipeline-Weighted Forecast** — Apply stage-specific close rates to your current pipeline 2. **Cohort Analysis** — Track revenue by customer cohort with expansion/contraction/churn 3. **Scenario Modeling** — Bear/base/bull project","codeSnippets":[],"executableExamples":[{"language":"text","snippet":"Month 0: New MRR from cohort\nMonth 1: Retained MRR × (1 - monthly churn rate)\nMonth 3: Add expansion revenue (avg 2-5% monthly for healthy SaaS)\nMonth 6: Steady-state retention rate applies\nMonth 12: Mature cohort — use net revenue retention"},{"language":"text","snippet":"REVENUE FORECAST — [Period]\n================================\nCurrent ARR: $X\nPipeline (Weighted): $X\nExpected New ARR: $X\n\n12-Month Projection:\n  Bear:  $X (20%)\n  Base:  $X (60%)\n  Bull:  $X (20%)\n  Expected: $X\n\nKey Risks:\n  1. [Risk] — [Mitigation]\n  2. [Risk] — [Mitigation]\n\nLeading Indicators:\n  🟢 [Healthy metric]\n  🟡 [Watch metric]\n  🔴 [Concerning metric]\n\nNext Month Actions:\n  1. [Specific action]\n  2. [Specific action]"}],"parameters":{},"dependencies":[],"permissions":[],"extractedFiles":[],"languages":["typescript"],"docsSourceLabel":"CLAWHUB","editorialOverview":"Revenue Forecasting Engine Revenue Forecasting Engine Build accurate, data-driven revenue forecasts your board and investors actually trust. What This Does Generates a complete revenue forecasting model covering: 1. **Pipeline-Weighted Forecast** — Apply stage-specific close rates to your current pipeline 2. **Cohort Analysis** — Track revenue by customer cohort with expansion/contraction/churn 3. **Scenario Modeling** — Bear/base/bull project","editorialQuality":{"score":100,"threshold":65,"status":"ready","wordCount":371,"uniquenessScore":67,"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":"2026-10-09T23:47:40.825Z","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. Unified access to frontier LLMs","url":"https://github.com/CherryHQ/cherry-studio","homepage":"https://cherry-ai.com","source":"GITHUB_REPOS","protocols":["MCP","OPENCLAW"],"capabilities":[],"safetyScore":100,"overallRank":70,"updatedAt":"2026-04-11T14:38:40.986Z","createdAt":"2026-02-25T03:38:19.379Z","downloads":null},{"id":"6f6582d0-5d76-4f0f-b81d-86520247950b","entityType":"agent","canonicalPath":"/agent/copilotkit-copilotkit","slug":"copilotkit-copilotkit","name":"CopilotKit","description":"The Frontend for Agents & Generative UI. React + Angular","url":"https://github.com/CopilotKit/CopilotKit","homepage":"https://docs.copilotkit.ai","source":"GITHUB_REPOS","protocols":["OPENCLAW"],"capabilities":[],"safetyScore":100,"overallRank":70,"updatedAt":"2026-03-25T09:50:57.846Z","createdAt":"2026-02-25T03:39:14.617Z","downloads":null}],"links":{"hub":"/agent","source":"/agent/source/clawhub","protocols":[{"label":"OpenClaw","href":"/agent/protocol/openclew"}]}}}