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Skill

/analyze-heterogeneity

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

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de-anthropocentric-research-engine
499200 skills
Install
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill analyze-heterogeneity --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/analyze-heterogeneity

Context preview

The summary Claude sees to decide when to auto-load this skill.

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

SKILL.md

analyze-heterogeneity.SKILL.md
name: analyze-heterogeneity
description: "Identify clinical, methodological, and statistical heterogeneity sources and prioritize subgroup/meta-regression/outlier investigation."

analyze-heterogeneity

Purpose

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

Input contract

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

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`
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Ships withde-anthropocentric-research-engine

The complete research orchestration system for AI-native science. What It Does Design Philosophy Architecture (v3.2.2) Quick Start Configuration Roadmap License DARE is not a tool that helps you do research. It is the researcher.

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Python
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Apache-2.0
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4h ago
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7mo ago
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Repo: yogsoth-ai/de-anthropocentric-research-engine