Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
Version History
v2.0: Multi-model parallel research (Gemini+o3+Opus+MiniMax), framework-driven reasoning with 12+ strategy frameworks, agreement matrix cross-validation, confidence scoring
What This Skill Does
Runs 4 AI models in parallel (Gemini 2.5 Pro, o3, Claude Opus 4, MiniMax M2.5), each applying a relevant analytical framework to the research question, then cross-validates findings across models and merges them into a cited report with an agreement matrix. Covers competitive strategy, market sizing, investment analysis, product strategy, and other structured question types. Outputs markdown and PDF.
Running 4 models with different strengths in parallel and cross-validating their outputs catches conflicting claims and errors that any single model would miss.
When to use it
- Analyzing competitive dynamics before entering a new market
- Investment due diligence on a startup or public company
- Evaluating whether to build or buy a technology component
- Sizing a market for a new product pitch
- Researching regulatory and risk landscape for a business decision
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: Research the competitive landscape for AI coding assistants
- 1Selects Porter's Five Forces and 7 Powers as applicable frameworks for the question
- 2Decomposes the topic into 6 sub-questions covering key players, switching costs, differentiation, and market share
- 3Spawns 4 model agents in parallel, each instructed to apply the frameworks and run at least 10 web searches
- 4Builds an agreement matrix comparing key claims across all 4 model outputs and resolves conflicts by checking source quality
- 5Merges findings into a structured report with inline citations and saves it as a PDF
A markdown report with framework analysis, agreement matrix, model disagreements section, and 60+ cited sources, delivered as a PDF