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/us-undervalued-growth-screener

@b9ca9a4

Autonomously screen NYSE, Nasdaq, and NYSE American operating-company stocks for undervalued-growth/GARP opportunities using forward same-basis valuation, driver-derived EPS/FCF forecasts, primary-source financial verification, SBC and dilution controls, sector and cycle normalization, auditable candidate-pool coverage, and fail-closed final reporting. Use when asked to find, screen, rank, or refresh US undervalued-growth stocks, including minimal requests with no ticker list or parameters.

Use this Skill: https://skilld.dev/gh/tradermonty/claude-trading-skills/us-undervalued-growth-screener

This session only. Nothing lands on disk.

referencesmigration-v2-to-v3.md

≈640 tokens on demand. Your agent reads this file only when SKILL.md points to it.

Migration from Schema v2 to v3

Breaking Changes

Schema v3 makes the research run—not just each candidate—auditable and finalizable.

New top-level requirements

  • market_context must contain current numeric context and source IDs.
  • global_sources must use the strict source ledger schema.
  • screening_audit must reference or embed a hash-verifiable row-level universe artifact.
  • run_metadata.status = complete is valid only when every selected broad-screen symbol has a candidate record.

Source ledger

supports changed from an informal string to a required array:

{"supports": ["latest_earnings", "financials.cash_flow_ttm"]}

Source kind and tier must be compatible. Third-party transcripts are not company IR.

Latest earnings

Replace a single mixed record with separate records:

{
  "latest_report_type": "annual",
  "quarter": {"period_type": "quarter", "period": "Q4 FY2026"},
  "full_year": {"period_type": "full_year", "period": "FY2026"}
}

Formal valuation basis

The current formal period must be ntm or fy1. A TTM metric may be supplemental but cannot drive the constant-multiple ranking scenario.

Estimate breadth

A consensus horizon with fewer than the configured minimum analysts is supplemental unless accompanied by a fully sourced independent model.

Cash and EV/FCF

EV now uses:

market cap + total debt - corporate cash - eligible marketable securities

Customer/settlement funds and restricted cash are excluded from shareholder-available cash.

New sector controls

  • Commercial biopharma concentration may be derived from product and total revenue.
  • Near-LOE concentrated franchises receive 6x and 8x stress scenarios.
  • Auto dealerships require floorplan-adjusted leverage.
  • Payments require corporate/settlement cash separation.

New scripts and flags

  • screen_universe.py: complete row-level broad-screen audit.
  • research_contract.py: schema-v3 validation.
  • evaluate_candidates.py --require-final: exit 2 for a provisional or globally invalid run after writing diagnostics.

Migration Procedure

  1. Create current market context and global source files.
  2. Run the broad-screen audit script.
  3. Initialize a new v3 run; do not mutate a v2 state directory in place.
  4. Convert earnings records and forward periods.
  5. Correct source supports types and source classifications.
  6. Reconcile cash/debt and forward forecast bases.
  7. Save every selected candidate.
  8. Run strict evaluation with --require-final.

Source: SKILL.md on GitHub

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  • Gen Agent Trust Hub5d

    The skill is a professional-grade stock screening tool that implements rigorous data integrity checks and professional financial modeling. It uses local Python scripts to handle large data payloads from well-known financial APIs (Financial Modeling Prep and the SEC), keeping raw data out of the AI's immediate context. Security features include proactive filtering to prevent the inclusion of secrets or environment files in generated audit bundles.

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    Risk: LOW · No issues

Signed by skilld at b9ca9a4. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub 18 hours ago.

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