Paper Claim Audit

# Paper Claim Audit: Zero-Context Evidence Verification

Verify that every claim in the paper matches raw evidence for: **$ARGUMENTS**

## Why This Exists

The executor writes experiments AND writes the paper. It "knows" what the results should be. This creates confirmation bias:
- Rounding 84.7% up to 85.3%
- Reporting best seed instead of average
- Citing metrics from a different experiment config
- Claiming "improves by 15%" when the delta is actually 12.8%

A **fresh reviewer with zero prior context** catches these because it has no expectations — it just compares paper text vs raw files.

## How This Differs From Other Audit Skills

| Skill | Question it answers |
|-------|-------------------|
| `/experiment-audit` | Is the experiment code honest? (fake GT, normalization fraud) |
| `/result-to-claim` | Does the data scientifically support this claim? |
| **`/paper-claim-audit`** | **Does the paper report the data truthfully and precisely?** |

## Core Principle

**Zero-context, fresh reviewer.** The auditor receives ONLY:
- Paper .tex files (the claims)
- Raw result files (the evidence)

It does NOT receive:
- ❌ EXPERIMENT_LOG.md
- ❌ EXPERIMENT_TRACKER.md
- ❌ AUTO_REVIEW.md
- ❌ NARRATIVE_REPORT.md
- ❌ Any executor summary or interpretation
- ❌ Any prior audit results
- ❌ Any conversation history

This is **stricter than reviewer-independence** — it's zero-context evidence audit.

## Workflow

### Step 1: Collect Files (Executor — Claude)

Locate paper and result files WITHOUT reading or interpreting them.

**Paper files** (claims) — paths shown relative to the shell's working
directory so you can find them with `ls`; when writing them into
`audited_input_hashes`, use paths relative to the paper dir (no `paper/`
prefix) per the "Submission Artifact Emission" section below:
```