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/identify-shared-priors

Trace supposedly independent evidence/reasoning paths to shared priors, datasets, models, prompts, framings, assumptions, or upstream sources that induce correlated errors.

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de-anthropocentric-research-engine
499200 skills
Install
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill identify-shared-priors --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/identify-shared-priors

Context preview

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

Trace supposedly independent evidence/reasoning paths to shared priors, datasets, models, prompts, framings, assumptions, or upstream sources that induce correlated errors.

SKILL.md

identify-shared-priors.SKILL.md
name: identify-shared-priors
description: "Trace supposedly independent evidence/reasoning paths to shared priors, datasets, models, prompts, framings, assumptions, or upstream sources that induce correlated errors."

identify-shared-priors

Purpose

Trace supposedly independent paths to shared priors, datasets, models, prompts, framings, assumptions, or upstream sources.

Input contract

required: [evidence_paths, provenance_records]
optional: [prompt_records, model_records, upstream_sources]
constraints: [shared dependency identity and path membership must be explicit]

Procedure

1. Inventory each path's inputs and assumptions. 2. Match shared priors, data, models, prompts, framing, and upstream evidence. 3. Produce dependency clusters and unresolved provenance.

If shared priors and dependence groups are explicit, consider `estimate-effective-evidence-count` as the next tactic.

Output contract

produces: [shared_prior_map, dependency_clusters, unresolved_links]
delta_fields: [findings, evidence_updates, uncertainties, open_questions]

Quality gates

  • Similar conclusions alone are not evidence of shared priors; trace the dependency.

Failure and counterexamples

Mark provenance unknown rather than inferring common origin from naming similarity.

Provenance map

  • resolved: independent-convergence-audit
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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Repo: yogsoth-ai/de-anthropocentric-research-engine