full-paper-audit
Audit the entire paper -- cross-section consistency, all citations, all style issues
/plugin install ai-asset-pricingdetails
Full Paper Audit Skill
Comprehensive audit of the entire paper for style compliance, factual consistency, citation correctness, and cross-section coherence.
Examples
/full-paper-audit-- run complete audit/full-paper-audit --focus style-- style-only pass/full-paper-audit --focus citations-- citation-only pass
Workflow
Step 1: Load All Context
- Read
.claude/rules/academic-writing.md - Read
.claude/rules/banned-words.md - Read
guidance/paper-context.md(if it exists) - Read
.claude/rules/latex-citations.md(if it exists) - Read
main.texin full
Step 2: Section-by-Section Audit
Discover sections by scanning for %% BEGIN: / %% END: markers in main.tex. Run /audit-section on each section sequentially.
Step 2b: Math Audit
For sections containing formal environments (any section with \begin{proposition}, \begin{theorem}, \begin{lemma}, or \begin{proof}), run /audit-math. Include SEVERITY SUMMARY and TOP PRIORITY FIXES in the master report.
Step 2c: Editorial Artifact Scan
Before proceeding to cross-section checks, grep the full manuscript for submission-blocking editorial artifacts in active prose (not LaTeX % comments):
[HUMAN EDIT,TODO,FIXME,XXX,[TBD],[PLACEHOLDER],[INSERT- Parenthetical editing notes:
(change to,(should be,(need to,(fix this),(update this) - Missing-reference markers:
[??],[?],[cite],[ref]Any hit is Critical and goes to the top of the priority fixes list.
Step 3: Cross-Section Consistency
Check that the SAME numbers are used consistently everywhere:
- Do quantitative claims in the introduction match those in the results sections?
- Does the conclusion match the findings reported in the body?
- Are terminology choices consistent across all sections?
- Are counts (sample size, number of variables, etc.) consistent everywhere they appear?
If guidance/paper-context.md exists, cross-reference all claims against its canonical values.
Step 3b: Caption Consistency
Run /audit-captions to check caption-level consistency. Include CRITICAL and IMPORTANT findings in the master report.
Step 4: Cross-Reference Audit
- Check all
\ref{}and\eqref{}resolve to valid labels - Check all tables and figures are referenced in text
- Check no orphaned labels exist
Step 5: Citation Completeness
- Check all
\cite{}keys exist in .bib - Check all .bib entries are actually cited (flag unused entries)
- Verify key citations via Perplexity (batch mode, high-priority entries first)
Step 6: Compile Master Report
Step 6b: Aggregate AI-Tell Statistics
After section-by-section audit, run a paper-wide pass for patterns that only emerge at scale:
- AI-marker word frequency: Count total occurrences of all Kobak/Gray/Liang markers across the full paper. Report density per 1000 words. Flag if >2 per 1000 words.
- Transition diversity: List all paragraph-opening words/phrases. Flag if any single opener appears 3+ times.
- "By contrast" / "In contrast" density: Flag if >3 uses paper-wide.
- Soft-ban accumulation: Sum all soft-ban word uses across sections. Flag if total exceeds 10.
- Sentence length distribution: Sample 20 paragraphs. Report coefficient of variation in sentence length. Flag if CV < 0.25 (too uniform).
- Intensive reflexive count: Count "itself"/"themselves" paper-wide. Flag if >4.
Output
FULL PAPER AUDIT
=================
OVERVIEW:
- Total issues: N
- Critical: M
- Suggestions: K
- Sections audited: [N body + M appendices]
CROSS-SECTION CONSISTENCY:
- [list of inconsistencies]
STYLE SUMMARY BY SECTION:
| Section | Banned Words | Passive | Vague Claims | Terminology | Total |
|---------|-------------|---------|--------------|-------------|-------|
| [name] | ... | ... | ... | ... | ... |
[etc.]
CITATION AUDIT:
- Total citations: N
- Verified: X
- Flagged: Y
CROSS-REFERENCES:
- Resolved: X
- Broken: Y
AI-TELL STATISTICS:
- AI-marker words: N (density: X per 1000 words)
- Unique paragraph openers: N out of M paragraphs
- Soft-ban total: N uses
- Sentence length CV: X (target: >0.30)
TOP 10 PRIORITY FIXES:
1. [most important issue]
[etc.]
technical
- github
- Alexander-M-Dickerson/ai-asset-pricing
- stars
- 49
- license
- MIT
- contributors
- 1
- last commit
- 2026-04-19T07:58:01Z
- file
- .claude/skills/full-paper-audit/SKILL.md