math

Name: math
Author: docxology

tests for the math module (population genetics, Bayesian, decision theory…). Files (verified 2026-09-05): 28 test modules + `__init__.py`, covering population genetics (coalescent, demography, effecti

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About

Imported from docxology/MetaInformAnt (tests/math/AGENTS.md). Install upstream with npx skills add docxology/MetaInformAnt --skill math. Copyright stays with the author.

AGENTS.md — `MetaInformAnt/tests/math/`

tests for the math module (population genetics, Bayesian, decision theory…). Files (verified 2026-09-05): 28 test modules + __init__.py, covering population genetics (coalescent, demography, effective size, Fst, LD, selection, statistics, popgen shim), core utilities, Bayesian inference, decision theory, epidemiology, evolutionary dynamics, perception, and quantitative genetics.

Conventions

Real implementations with small deterministic data; the lexical no-mocks gate applies (no MagicMock/unittest.mock).
Run: env -u VIRTUAL_ENV .venv/bin/python -m pytest -q tests/math -p no:cacheprovider (verified 2026-09-05: 274 passed pre-review). Repo-wide policy: see the repository-root AGENTS.md.

Use it

Copy one of these into your project. Installing also returns the manifest and these snippets.

yaml

targets:
  - https://api.opensmartroute.ai/api/v1/registry/docxology-metainformant-math/manifest   # or paste the manifest below

Manifest

An Open Capability Manifest: the router reads it to know what this does, what it costs and when to pick it.

docxology-metainformant-math.ocm.jsonjson

{
  "ocm": "1",
  "id": "docxology-metainformant-math",
  "kind": "skill",
  "name": "math",
  "description": "tests for the math module (population genetics, Bayesian, decision theory…). Files (verified 2026-09-05): 28 test modules + `__init__.py`, covering population genetics (coalescent, demography, effective size, Fst, LD, selection, statistics, popgen shim), core utilities, Bayesian inference, decision theory, epidemiology, evolutionary dynamics, perception, and quantitative genetics.",
  "publisher": "docxology",
  "version": "1.0.0",
  "capabilities": {
    "domains": [
      "coding",
      "math"
    ],
    "tags": [
      "skill-md",
      "github-agents"
    ],
    "languages": [
      "en"
    ]
  },
  "quality_prior": 0.6,
  "examples": [
    "tests for the math module (population genetics, Bayesian, decision theory…). Files (verified 2026-09-05): 28 test modules + `__init__.py`, covering population genetics (coalescent, demography, effective size, Fst, LD, selection, statistics, popgen shim), core utilities, Bayesian inference, decision theory, epidemiology, evolutionary dynamics, perception, and quantitative genetics."
  ],
  "primary": false,
  "metadata": {
    "source": {
      "provider": "github-agents",
      "repository": "https://github.com/docxology/MetaInformAnt",
      "path": "tests/math/AGENTS.md",
      "ref": "524660cd2c21f84c04fd32700cb6e6a9c2a35a86",
      "url": "https://github.com/docxology/MetaInformAnt/blob/524660cd2c21f84c04fd32700cb6e6a9c2a35a86/tests/math/AGENTS.md",
      "key": "docxology/MetaInformAnt/tests/math/AGENTS.md"
    }
  },
  "instructions": "# AGENTS.md — `MetaInformAnt/tests/math/`\n\ntests for the math module (population genetics, Bayesian, decision theory…).\nFiles (verified 2026-09-05): 28 test modules + `__init__.py`, covering population genetics (coalescent, demography, effective size, Fst, LD, selection, statistics, popgen shim), core utilities, Bayesian inference, decision theory, epidemiology, evolutionary dynamics, perception, and quantitative genetics.\n\n\n## Conventions\n- Real implementations with small deterministic data; the lexical no-mocks gate\n  applies (no `MagicMock`/`unittest.mock`).\n- Run: `env -u VIRTUAL_ENV .venv",
  "cost": {
    "context_tokens": 189
  }
}

Fetch it by URL: GET /api/v1/registry/docxology-metainformant-math/manifest?version=1.0.0

About

AGENTS.md — MetaInformAnt/tests/math/

Conventions

Use it

Manifest

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AGENTS.md — `MetaInformAnt/tests/math/`