ClawHub

strategic-analyst-skill

Data & APIs

Provides McKinsey-style industry and market analysis using classic frameworks to support strategic, investment, and market entry decisions with data-backed r...

Install

openclaw skills install strategic-analyst-skill

Strategic Analyst

A McKinsey-style strategic analysis assistant that helps executives, investors, students, and industry entrants build systematic industry认知 and make data-driven decisions.

When to Use

Activate this skill when the user needs:

  • Industry analysis or market research
  • Competitive landscape assessment
  • Market entry strategy support
  • Investment decision backing
  • Strategic framework application (Porter's Five Forces, TAM-SAM-SOM, PESTEL, etc.)

Typical triggers:

  • "帮我分析XX行业"
  • "战略分析"
  • "竞争格局"
  • "市场研究"
  • "麦肯锡"
  • "进入XX行业"

How It Works

  1. Needs Diagnosis: Identify user identity (CEO/executive/student/entrant) and core decision problem.
  2. Multi-source Data Collection: Auto-search latest industry data via Tavily/WebSearch. Extract tables from PDFs, dynamic web pages, and images (OCR).
  3. Framework-driven Analysis: Apply 6 classic frameworks:
    • Industry Structure (Porter's Five Forces)
    • Market Sizing (TAM-SAM-SOM)
    • Competitive Landscape
    • Trend Analysis (PESTEL)
    • Value Chain
    • Key Success Factors
  4. Mandatory Artifact: Save data_collection.md — a forced intermediate log of all search queries, tools used, source URLs, and raw snippets.
  5. Report Generation: Output both Markdown and HTML reports. HTML tables support hover-to-download PNG/SVG buttons.
  6. Quality Gate: Auto-check structure, framework usage, professional tone, data backing, and source-link completeness before delivery.

Key Files

  • skill.yaml — Skill configuration
  • agent_instructions.md — Agent persona, data transparency rules, and professional boundaries
  • tools/data_collector.py — Structured data collection with source URLs and credibility ratings
  • tools/report_generator.py — Dual-format report generator (Markdown + HTML) with table-download JS
  • tools/quality_gate.py — Automated quality checks
  • frameworks/ — 6 analysis framework templates
  • templates/ — Report templates (executive summary, student edition, full report)
  • checklists/ — Pre-analysis, data collection, quality check, and boundary checklists
  • data_sources/ — General and industry-specific data source guides

Prerequisites

Tavily API Key is required for deep research-grade search.

  • Sign up at https://tavily.com to get an API key.
  • Add it to settings.json under mcpServers.tavily:
{
  "mcpServers": {
    "tavily": {
      "command": "npx",
      "args": ["-y", "tavily-mcp@0.1.4"],
      "env": {
        "TAVILY_API_KEY": "tvly-your-api-key"
      }
    }
  }
}

If Tavily is not configured, the skill will fall back to WebSearch, but deep research capabilities will be limited.

Output Standards

  • All key data (market size, growth forecasts, competitive shares) must include source links in [source](URL) Markdown format.
  • Credibility star ratings (★★★★★ to ★☆☆☆☆) are required for every data point.
  • HTML reports use a professional black/red/gray financial-research style with clickable source links and table image downloads.
  • No "action list" or "next steps" sections per style guide.
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