abstract-structure
Remove domain surface details to expose transferable relational/mechanistic structure at a chosen abstraction level.
Trace supposedly independent evidence/reasoning paths to shared priors, datasets, models, prompts, framings, assumptions, or upstream sources that induce correlated errors.
Claude Code
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill identify-shared-priors --agent claude-code
Codex
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill identify-shared-priors -a codex -y
Cursor
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill identify-shared-priors -a cursor -y
Gemini CLI
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill identify-shared-priors -a gemini-cli -y
GitHub Copilot
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill identify-shared-priors -a github-copilot -y
OpenCode
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill identify-shared-priors -a opencode -y
Windsurf
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill identify-shared-priors -a windsurf -y
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."
Trace supposedly independent paths to shared priors, datasets, models, prompts, framings, assumptions, or upstream sources.
required: [evidence_paths, provenance_records] optional: [prompt_records, model_records, upstream_sources] constraints: [shared dependency identity and path membership must be explicit]
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.
produces: [shared_prior_map, dependency_clusters, unresolved_links] delta_fields: [findings, evidence_updates, uncertainties, open_questions]
Mark provenance unknown rather than inferring common origin from naming similarity.
A research skill graph for AI-native science. 271 markdown files. No runtime, no dependencies, no build step.
Remove domain surface details to expose transferable relational/mechanistic structure at a chosen abstraction level.
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