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alphagbm-stock-analysis

alphagbm-stock-analysis

github.com/alphagbmOther2.8k56 installsUpdated 5w ago
Repository

About alphagbm-stock-analysis

Stock Analysis is a focused Python runner for retrieving stock analysis through the ALPHAGBM API. It is for users who need evidence-preserving results and explicit handling of errors, missing data, and usage approval.

Key features

  1. 01Self-contained Python 3.9+ runner
  2. 02Retrieves stock analysis via API
  3. 03Preserves asset identity, dates, and units
  4. 04Reports missing data and score type
  5. 05Requires approval for shared allowance usage
  6. 06Surfaces failures without demo-data fallback

Use cases

  1. 01Retrieving an NVDA stock analysis
  2. 02Reviewing risk scores and volatility fields
  3. 03Handling missing data without fabricating metrics

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/alphagbm/skills --skill alphagbm-stock-analysis

After installing, type/alphagbm-stock-analysisin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

agents/
openai.yaml
references/
access.md
scripts/
review_engine.py
run.py

Details

From the project README

Stock Analysis

Read access and evidence rules first. This package is a focused function; full research workflows are listed in the repository catalogue. Its runner is self-contained and requires only Python 3.9+.

python3 "<skill-dir>/scripts/run.py" stock NVDA --confirm-usage

Requires ALPHAGBM_API_KEY. If the command uses --confirm-usage, first obtain approval to use the shared account allowance. Snapshot reads do not consume analysis credits, but still require account access.

Return only the successful API response, with its original asset identity, dates, units, missing-data flags and score type. Stock risk scores are not opportunity scores. Volatility fields can be missing; do not turn a snapshot into a fabricated 252-day IV Rank. Option candidates are not guaranteed fills or trade instructions. Never fall back silently to demo data. Nonzero exit must be surfaced as an error.

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