evidence-calibration-review

Solid

Use when you want a per-claim evidence-tier audit on a text artifact before it ships — assign T1-T6 tiers to every load-bearing claim, surface calibration mismatches (high confidence on weak evidence, or honesty-theater under-claiming), and flag P11 (citation-as-decoration), P17 (pile-of-anecdotes-as-evidence), P54 (unverifiable single-source) patterns. Encodes the Evidence & Calibration deliberator role from the agent-council 5-perspective quality gate. Use standalone for fast evidence audit, or compose with the other 4 deliberator skills.

Code & Development 9 stars 1 forks Updated 1 weeks ago MIT

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Quality Score: 83/100

Stars 20%
33
Recency 20%
90
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
80
License 10%
100
Description 5%
100

Skill Content

## Purpose Run a per-claim evidence-tier audit on a text artifact before it ships. The Evidence & Calibration role reads the artifact claim by claim and asks one question per claim: **what tier of evidence supports it, and is the artifact's stated confidence consistent with that tier?** A claim asserted with high confidence on Tier 6 (inferred) evidence is a calibration failure. A claim hedged with "perhaps" when the evidence is Tier 1 (primary source, verified) is also a calibration failure — under-claiming is its own honesty failure. The skill catches both directions. This is the boring and the load-bearing role on the panel. "Where is the source for X?" is the question that ends careers. Evidence & Calibration surfaces every unsourced claim before it ships. The skill encodes the Evidence & Calibration role from the `agent-council` 5-deliberator quality gate. Use standalone for fast evidence audit, or compose with the other 4 deliberator skills for fuller coverage. ## When to Use / When NOT to Use **Use this skill when:** - A claim-dense artifact (analysis, memo, public pitch) is about to ship and you want every load-bearing claim tiered - You suspect over-claiming (high confidence on weak evidence) or under-claiming (hedging what is actually verified) and want both directions surfaced - A piece relies on attributions ("X said Y" / "Microsoft did Z") and you want each verified or hedged appropriately - You need to catch P11 (citation-as-decoration), P17 (pile-of-anecd...

Details

Author
Avyayalaya
Repository
Avyayalaya/agent-council
Created
2 months ago
Last Updated
1 weeks ago
Language
Python
License
MIT

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