estimate-effective-evidence-count
Estimate an effective number of independent evidence/reasoning paths after discounting dependence/correlation; report nominal N, dependence structure, and…
Skill by yogsoth-ai
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
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About
Use cases: documents, deep-research, data-analysis
Reviews
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What this skill can do and what it asks for, from its SKILL.md and code. Checked Oct 26, 2026.
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Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/estimate-effective-evidence-count
What's inside
- Skill name
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.
- License
- Apache-2.0
- Instructions
- 26 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# estimate-effective-evidence-count ## Purpose Estimate independent evidence count after discounting dependence and correlation. ## Input contract ```yaml 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 ```yaml 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
From yogsoth-ai/de-anthropocentric-research-engine, Apache-2.0.
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Signals
- Stars
- 505
- Forks
- 43
- Open issues
- 1
- Last commit (this folder)
- Sep 23, 2026 (1 month ago)
- Last release
- Oct 23, 2026 (5 days ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- Apache-2.0
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
estimate-effective-evidence-count skill. Agent Mart. https://agentmart.dev/skills/yogsoth-ai-estimate-effective-evidence-count (last updated 2026-10-24)