competitive

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Competitive landscape analysis, competitor comparison, peer positioning, market share dynamics, competitive moat assessment, Porter five forces, industry competition, competitive advantage analysis, market positioning, strategic group mapping, compare competitors

AI & Automation 204 stars 16 forks Updated today Apache-2.0

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Quality Score: 94/100

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Description 5%
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Skill Content

<!-- analog: sector-overview --> ## Preflight Run the canonical pre-flight sequence — MCP health probe, ticker resolution, workspace `style.md` override, memory load, and coverage check. See `contracts/preflight.md`. Include the `X-Agentii-Trace` header on every tool call per `contracts/x-agentii-trace-header.md`. ## Triggers - analyze dim competitive landscape - run dim competitive landscape analysis - produce dim competitive landscape report - dim competitive landscape breakdown - dim competitive landscape deep dive - build a dim competitive landscape - assess dim competitive landscape - quantify dim competitive landscape - compare dim competitive landscape across peers - review dim competitive landscape for - generate dim competitive landscape on - dim competitive landscape for investment decision ## Defaults | Parameter | Default | Notes | |---|---|---| | lookback_years | 3 | Historical data window | | include_peers | false | Whether to surface a peer comparison block | <!-- BEGIN port-dimension-prompts methodology + modes --> ## Methodology ### Retrieval Scope This skill performs unstructured document search at scale (10-K, 10-Q, 8-K filings and earnings call transcripts spanning multiple fiscal periods). The three-layer agent-use-ready retrieval protocol (Document Discovery → Page Map → Deep Read) applies to all unstructured document search at scale. ### Retrieval Strategy Follow the retrieval strategy decision tree in `contracts/retrieval.md`. This skill us...

Details

Author
agentii-ai
Repository
agentii-ai/agentii-investment-intelligence
Created
4 months ago
Last Updated
today
Language
Python
License
Apache-2.0

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