abstract-structure
Remove domain surface details to expose transferable relational/mechanistic structure at a chosen abstraction level.
@yogsoth-aiInstall SkillAutomation
Skill
/estimate-effective-evidence-count
Estimate an effective number of independent evidence/reasoning paths after discounting dependence/correlation; report nominal N, dependence structure, and N_eff.
Claude Code
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill estimate-effective-evidence-count --agent claude-code
Codex
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill estimate-effective-evidence-count -a codex -y
Cursor
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill estimate-effective-evidence-count -a cursor -y
Gemini CLI
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill estimate-effective-evidence-count -a gemini-cli -y
GitHub Copilot
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill estimate-effective-evidence-count -a github-copilot -y
OpenCode
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill estimate-effective-evidence-count -a opencode -y
Windsurf
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill estimate-effective-evidence-count -a windsurf -y
SKILL.md
estimate-effective-evidence-count.SKILL.mdname: estimate-effective-evidence-count description: "Estimate an effective number of independent evidence/reasoning paths after discounting dependence/correlation; report nominal N, dependence structure, and N_eff."
estimate-effective-evidence-count
Purpose
Estimate independent evidence count after discounting dependence and correlation.
Input contract
required: [evidence_paths, dependence_structure] optional: [correlation_estimates, nominal_count] constraints: [dependence assumptions and uncertainty must be explicit]
Procedure
1. Count nominal paths and trace shared dependencies. 2. Assign dependence classes or correlations. 3. Estimate N_eff and sensitivity to dependence assumptions.
Output contract
produces: [nominal_count, dependence_map, effective_count, sensitivity_range] delta_fields: [findings, evidence_updates, uncertainties, decisions]
Quality gates
- Report N and N_eff separately; include a range when dependence is uncertain.
Failure and counterexamples
Do not inflate N_eff by counting repeated sources or shared models as independent.
Provenance map
- resolved: independent-convergence-audit
Ships withde-anthropocentric-research-engine
A research skill graph for AI-native science. 271 markdown files. No runtime, no dependencies, no build step.
512200 skills
Stars on GitHub
Momentum
- stars in total
- 512
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Questions about estimate-effective-evidence-count.
- Which coding agents can use estimate-effective-evidence-count?
- estimate-effective-evidence-count installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.