abstract-structure
Remove domain surface details to expose transferable relational/mechanistic structure at a chosen abstraction level.
Test whether a proposed cause/mechanism is necessary and/or sufficient under controlled counterfactual or intervention comparisons.
Claude Code
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill evaluate-necessity-sufficiency --agent claude-code
Codex
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill evaluate-necessity-sufficiency -a codex -y
Cursor
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill evaluate-necessity-sufficiency -a cursor -y
Gemini CLI
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill evaluate-necessity-sufficiency -a gemini-cli -y
GitHub Copilot
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill evaluate-necessity-sufficiency -a github-copilot -y
OpenCode
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill evaluate-necessity-sufficiency -a opencode -y
Windsurf
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill evaluate-necessity-sufficiency -a windsurf -y
name: evaluate-necessity-sufficiency description: "Test whether a proposed cause/mechanism is necessary and/or sufficient under controlled counterfactual or intervention comparisons."
Test whether a proposed cause or mechanism is necessary and/or sufficient under controlled counterfactual or intervention comparisons.
required: [cause_or_mechanism, outcome, comparison_conditions] optional: [counterfactual_worlds, intervention_data] constraints: [necessary and sufficient tests must be reported separately]
1. Define removal/absence and presence/intervention contrasts. 2. Compare outcomes under held-fixed conditions. 3. Report necessity, sufficiency, confounds, and uncertainty.
produces: [necessity_result, sufficiency_result, comparison_table, confounds] delta_fields: [findings, evidence_updates, uncertainties, decisions]
Do not infer necessity from correlation or sufficiency from one positive case.
A research skill graph for AI-native science. 271 markdown files. No runtime, no dependencies, no build step.
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