earnings-sentiment

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Earnings sentiment analysis, analyst estimates vs guidance, earnings surprise history, consensus sentiment, earnings revision trends, analyst rating changes, earnings beat miss track record, guidance accuracy, whisper numbers, pre-announcement sentiment

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: catalyst-calendar --> ## 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 earnings sentiment - run dim earnings sentiment analysis - produce dim earnings sentiment report - dim earnings sentiment breakdown - dim earnings sentiment deep dive - build a dim earnings sentiment - assess dim earnings sentiment - quantify dim earnings sentiment - compare dim earnings sentiment across peers - review dim earnings sentiment for - generate dim earnings sentiment on - dim earnings sentiment 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 **Ownership & insider signals**: `search_institutional_holdings` (top-10 holders + whale portfolios, `direction=accumulat...

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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