Files
sickn33 0db870eb11 meta(risk): Sync conservative legacy labels
Add a maintainers script to safely promote high-confidence legacy risk labels from unknown to concrete values, cover it with tests, and regenerate the canonical skill artifacts and plugin copies. This reduces the legacy unknown backlog without forcing noisy classifications that still need manual review.
2026-03-29 10:45:21 +02:00

3.4 KiB

name, description, risk, source, date_added
name description risk source date_added
xvary-stock-research Thesis-driven equity analysis from public SEC EDGAR and market data; /analyze, /score, /compare workflows with bundled Python tools (Claude Code, Cursor, Codex). safe community 2026-03-23

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 latest annual + quarterly EDGAR datapoints.
  • Cite filing form/date whenever stating a hard financial figure.
  • Keep analysis concise but decision-oriented.
  • Use plain English, avoid generic finance fluff.
  • Never claim certainty; surface assumptions and kill criteria.

Output Format

For /analyze {ticker} use this shape:

  1. Verdict (Constructive / Neutral / Cautious)
  2. Conviction Rationale (3-5 bullets)
  3. XVARY Scores (Momentum, Stability, Financial Health, Upside)
  4. Thesis Pillars (3-5 pillars)
  5. Top Risks (3 items)
  6. Kill Criteria (thesis-invalidating conditions)
  7. Financial Snapshot (revenue, margin proxy, cash flow, leverage snapshot)
  8. Next Checks (what to watch over next 1-2 quarters)

For /score {ticker} use this shape:

  1. Score table
  2. Factor highlights by score
  3. Confidence note

For /compare {ticker1} vs {ticker2} use this shape:

  1. Score comparison table
  2. Where ticker A is stronger
  3. Where ticker B is stronger
  4. What would change the ranking

Scoring + Methodology References

  • Methodology: references/methodology.md
  • Score definitions: references/scoring.md
  • EDGAR usage guide: references/edgar-guide.md

Data Tooling

  • EDGAR tool: tools/edgar.py
  • Market tool: tools/market.py

If a tool call fails, state exactly what data is missing and continue with available inputs. Do not hallucinate missing figures.

Powered by XVARY Research | Full deep dive: xvary.com/stock/{ticker}/deep-dive/

Compliance Notes

  • This skill is research support, not investment advice.
  • Do not fabricate non-public data.
  • Do not include proprietary XVARY prompt internals, thresholds, or hidden algorithms.