xvary-stock-research

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Thesis-driven equity analysis from public SEC EDGAR and market data; /analyze, /score, /compare workflows with bundled Python tools (Claude Code, Cursor, Codex).

AI & Automation 39,350 stars 6386 forks Updated today MIT

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Skill Content

# XVARY Stock Research Skill Use this skill to produce institutional-depth stock analysis in Claude Code using public EDGAR + market data. ## When to Use - Use when you need a **verdict-style equity memo** (constructive / neutral / cautious) grounded in **public** filings and quotes. - Use when you want **named kill criteria** and a **four-pillar scorecard** (Momentum, Stability, Financial Health, Upside) without a paid data terminal. - Use when comparing two tickers with `/compare` and need a structured differential, not a prose-only chat answer. ## Commands ### `/analyze {ticker}` Run full skill workflow: 1. Pull SEC fundamentals and filing metadata from `tools/edgar.py`. 2. Pull quote and valuation context from `tools/market.py`. 3. Apply framework from `references/methodology.md`. 4. Compute scorecard using `references/scoring.md`. 5. Output structured analysis with verdict, pillars, risks, and kill criteria. ### `/score {ticker}` Run score-only workflow: 1. Pull minimum required EDGAR and market fields. 2. Compute Momentum, Stability, Financial Health, and Upside Estimate. 3. Return score table + short interpretation + top sensitivity checks. ### `/compare {ticker1} vs {ticker2}` Run side-by-side workflow: 1. Execute `/score` logic for both tickers. 2. Compare conviction drivers, key risks, and valuation asymmetry. 3. Return winner by setup quality, plus conditions that would flip the view. ## Execution Rules - Normalize all tickers to uppercase. - Prefer ...

Details

Author
sickn33
Repository
sickn33/antigravity-awesome-skills
Created
4 months ago
Last Updated
today
Language
Python
License
MIT

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