{
  "id": "python-numerical-scientific-correctness",
  "name": "python-numerical-scientific-correctness",
  "version": "0.1.0",
  "type": "skill",
  "provider": "python",
  "harnesses": [
    "codex",
    "claude-code",
    "cursor",
    "gemini",
    "kiro",
    "other"
  ],
  "summary": "Static review of Python numerical and scientific correctness: binary float used for money, rounding-mode errors, silent dtype coercion and integer overflow, missing-data (NaN) handling, timezone-naive timestamps, unseeded randomness and irreproducibility, numerical instability, and unbenchmarked vectorization claims. Reads source only; never runs the calculation.",
  "source_type": "original",
  "official_docs": [
    "https://docs.python.org/3/tutorial/floatingpoint.html",
    "https://docs.python.org/3/library/decimal.html",
    "https://pandas.pydata.org/docs/user_guide/timeseries.html#time-zone-handling",
    "https://numpy.org/doc/stable/reference/random/generator.html"
  ],
  "security_notes": "Static review only — reads Python/pandas/numpy source and sanitized sample schemas to locate money-as-float, rounding, dtype-coercion, timezone, and reproducibility defects; never runs the calculation, notebook, or benchmark and never observes an actual numeric result or timing. A claim about a computed value or a performance improvement is flagged as needing execution/benchmark evidence rather than asserted. Never requests production data or a live database/warehouse connection.",
  "last_verified": "2026-07-26",
  "path": "skills/python/python-numerical-scientific-correctness",
  "author": "github: VincentChuWaiChow"
}