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analyze-heterogeneity

Identify clinical, methodological, and statistical heterogeneity sources and prioritize subgroup/meta-regression/outlier investigation.

Skill by yogsoth-ai

IndexedApache-2.0★ 505
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/yogsoth-ai-analyze-heterogeneity

Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.

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About

Identify clinical, methodological, and statistical heterogeneity sources and prioritize subgroup/meta-regression/outlier investigation.

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Permissions

What this skill can do and what it asks for, from its SKILL.md and code. Checked Oct 26, 2026.

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Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/analyze-heterogeneity

What's inside

Skill name
analyze-heterogeneity
Description
Identify clinical, methodological, and statistical heterogeneity sources and prioritize subgroup/meta-regression/outlier investigation.
License
Apache-2.0
Instructions
45 lines in SKILL.md · view on GitHub

Files (1)

  • SKILL.md

SKILL.md (first lines)

# analyze-heterogeneity

## Purpose

Identify clinical, methodological, and statistical heterogeneity sources and prioritize subgroup, meta-regression, or outlier investigation.

## Input contract

```yaml
required: [evidence_records, outcome_schema, comparison_context]
optional: [covariate_schema, effect_estimates, subgroup_hypotheses]
constraints: [heterogeneity claims require record-level conditions and provenance]
```

## Procedure

1. Group records by declared design, population, intervention, outcome, and condition dimensions.
2. Compare effect or performance patterns within and across groups.
3. Identify plausible moderators, outliers, and confounding condition differences.
4. Prioritize subgroup or meta-regression investigations and record uncertainty.

If unexplained variation may reflect selective reporting rather than substantive moderators, consider `assess-publication-bias` as the next tactic.

## Output contract

```yaml
produces: [heterogeneity_sources, moderator_candidates, outlier_list, investigation_priorities]
delta_fields: [findings, evidence_updates, uncertainties, open_questions]
```

## Quality gates

- Each heterogeneity source must point to affected records and a comparison dimension.
- Do not infer a moderator from a single discrepant record without an uncertainty marker.

## Failure and counterexamples

Do not label ordinary measurement noise as a causal subgroup effect, and do not pool records whose condition vectors are incomparable.

## Provenance map

- `resolved: heterogeneity-source-analysis`
- `resolved: heterogeneity-investigation`

From yogsoth-ai/de-anthropocentric-research-engine, Apache-2.0.

More from yogsoth-ai/de-anthropocentric-research-engine

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Stars
505
Forks
43
Open issues
1
Last commit (this folder)
Sep 23, 2026 (1 month ago)
Last release
Oct 23, 2026 (5 days ago)

From GitHub (fetched Oct 24, 2026).

Details

License
Apache-2.0
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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Cite this page

analyze-heterogeneity skill. Agent Mart. https://agentmart.dev/skills/yogsoth-ai-analyze-heterogeneity (last updated 2026-10-24)