Full Paper 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.]