营收工作室
revenue-studio
by amoldericksoans
A revenue-first solofounder studio that watches markets, finds monetizable pain, validates offers, ships narrow products, and compounds commercial memory across launches. Uses massive parallel agent orchestration with 8 layers: Signal Mesh, Extraction, Opportunity Graph, Cofounder Council, Revenue Lab, Build Studio, Launch Loop, and Portfolio Allocator.
安装
claude skill add --url https://github.com/openclaw/skills文档
Revenue-First Solofounder Studio
A complete system for seeking revenue through disciplined stage-gated autonomy.
Architecture
8 Layers
- Signal Mesh - Collect market signals from X, Reddit, RSS, changelogs
- Commercial Extraction - Score pain severity and money signals
- Opportunity Graph - Build market structure from signals
- Cofounder Council - 7-agent decision making (CEO, PM, Skeptic, Economics, Monetization, Distribution, Research)
- Revenue Lab - Validate pricing, offers, and channels before build
- Build Studio - Ship narrow wedges with telemetry
- Launch Loop - Outbound, content, and demo execution
- Portfolio Allocator - Kill/pause/scale decisions
Key Principles
- Revenue-first - No build without monetization + distribution signoff
- Stage-gated - 7 stages from Observe to Scale/Kill, no skipping
- Parallel orchestration - Spawn 40+ agents for speed
- Memory continuity - Write-ahead logging for restart resilience
- Governance - Hard rules, approval gates, audit trails
Quick Start
# Spawn signal collection
openclaw spawn "collect market signals from X and Reddit"
# Run council review
openclaw spawn "run council review on thesis-001"
# Validate revenue hypothesis
openclaw spawn "create validation landing page for thesis-001"
Output Files
Located in revenue-studio/:
QUICKSTART.md- Operator's guideportfolio/thesis-001.md- First validated thesiscouncil/- 7 decision frameworksrevenue-lab/- Pricing, conversion, offer frameworksgovernance/- Rules, stage-gates, approvalssignals/- Market intelligencescoring/- RWOS calculator
Thesis Scoring
Revenue-Weighted Opportunity Score (RWOS):
RWOS = Pain × Frequency × Buyer Density × Purchase Intent ×
Speed-to-$ × Retention × Margin × Distribution × Expansion
− Penalties
Decision bands:
- 0-20: PASS
- 21-35: WEAK
- 36-50: MODERATE
- 51-65: STRONG
- 66-80: EXCELLENT
- 81-100: EXCEPTIONAL
相关 Skills
Claude API
by anthropic
Build, debug, and optimize Claude API / Anthropic SDK apps. Apps built with this skill should include prompt caching. Also handles migrating existing Claude API code between Claude model versions (4.5 → 4.6, 4.6 → 4.7, retired-model replacements). TRIGGER when: code imports `anthropic`/`@anthropic-ai/sdk`; user asks for the Claude API, Anthropic SDK, or Managed Agents; user adds/modifies/tunes a Claude feature (caching, thinking, compaction, tool use, batch, files, citations, memory) or model (Opus/Sonnet/Haiku) in a file; questions about prompt caching / cache hit rate in an Anthropic SDK project. SKIP: file imports `openai`/other-provider SDK, filename like `*-openai.py`/`*-generic.py`, provider-neutral code, general programming/ML.
并行代理
by axelhu
Use when facing 2 or more independent tasks that can be worked on without shared state - dispatches parallel subagents using sessions_spawn for concurrent investigation and execution, adapted for OpenClaw
高光制作器
by bwbernardweston18
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