evidence-auditor

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Audit the evidence supporting each claim and write gaps/concerns into `output/MISSING_EVIDENCE.md`.**Trigger**: evidence audit, missing evidence, unsupported claims, 审稿证据审计, 证据缺口.**Use when**: peer review 流程中，需要逐条检查 claim 的证据链、缺 baseline、评测薄弱点。**Skip if**: 缺少 claims 输入（例如还没有 `output/CLAIMS.md`）。**Network**: none.**Guardrail**: 只写“缺口/风险/下一步验证”，不要替作者补写论述或引入新主张。

⭐1stars🔀0forks📁View on GitHub🕐Updated Jan 8, 2026
[Academic Research]

When & Why to Use This Skill

The Evidence Auditor is a specialized Claude skill designed to enhance the rigor of academic writing and peer review. It systematically evaluates the evidence chain for every claim in a manuscript, identifying missing baselines, weak evaluation protocols, and unsupported assertions. By generating a detailed report of evidence gaps and actionable fixes, it helps researchers and reviewers ensure that every conclusion is backed by solid empirical or theoretical data.

Use Cases

  • Peer Review Preparation: Authors can use this skill to self-audit their manuscripts before submission to identify and address potential 'weak evidence' flags from reviewers.
  • Journal Reviewing: Reviewers can automate the tedious process of mapping claims to specific evidence in the text, allowing them to focus on high-level methodology and impact.
  • Technical Whitepaper Verification: Companies can audit technical reports to ensure that performance claims are supported by sufficient experimental data and appropriate baselines.
  • Research Quality Control: Research leads can use it to verify that conceptual definitions are unambiguous and that empirical claims do not exceed the scope of the provided evidence.
nameevidence-auditor
description|
**Trigger**evidence audit, missing evidence, unsupported claims, 审稿证据审计, 证据缺口.
**Use when**peer review 流程中，需要逐条检查 claim 的证据链、缺 baseline、评测薄弱点。
**Skip if**缺少 claims 输入（例如还没有 `output/CLAIMS.md`）。
**Network**none.
**Guardrail**只写“缺口/风险/下一步验证”，不要替作者补写论述或引入新主张。

Evidence Auditor (peer review)

Goal: for each claim, either (a) point to the supporting evidence in the manuscript, or (b) write a concrete gap with an actionable fix.

Inputs

  • output/CLAIMS.md

Outputs

  • output/MISSING_EVIDENCE.md

For each claim:

  • Claim: copy the claim text
  • Evidence present: what the paper provides (experiments/theory/citations)
  • Gap / concern: what is missing or weak
  • Minimal fix: the smallest additional evidence that would address the gap
  • Severity: major | minor (optional)

Workflow

  1. Iterate claims in output/CLAIMS.md.
  2. For empirical claims, check:
    • dataset/task definition is clear
    • baselines are appropriate
    • evaluation protocol is valid
    • ablations/sensitivity analyses exist where needed
  3. For conceptual claims, check:
    • definitions are unambiguous
    • assumptions are stated
    • claims do not exceed what is argued
  4. Write output/MISSING_EVIDENCE.md as a list of claim-by-claim entries.

Definition of Done

  • Every claim from output/CLAIMS.md has an evidence note or a gap item.
  • “Fix” items are actionable (what to add, not “more experiments”).

Troubleshooting

Issue: you cannot locate the evidence in the paper

Fix:

  • Mark the claim as “evidence not locatable” and ask for a clearer source pointer (or re-extract claims with better pointers).

Issue: the audit starts proposing new claims

Fix:

  • Stop; only critique what exists in output/CLAIMS.md and the manuscript.