mcpField
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alphagbm-iv-rank

alphagbm-iv-rank

github.com/alphagbmOther2.8k54 installsUpdated 5w ago
Repository

About alphagbm-iv-rank

alphagbm-iv-rank is a focused skill for retrieving a volatility snapshot through its Python runner. It requires account access and returns the successful API response without substituting demo data or treating risk scores as opportunity scores.

Key features

  1. 01Python 3.9+ self-contained runner
  2. 02Volatility snapshot retrieval
  3. 03Preserves response identity and data flags
  4. 04Requires ALPHAGBM_API_KEY

Use cases

  1. 01Retrieve a volatility snapshot for an asset
  2. 02Review returned dates, units, and missing-data flags

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/alphagbm/skills --skill alphagbm-iv-rank

After installing, type/alphagbm-iv-rankin 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

Volatility Snapshot

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" snapshot NVDA

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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