humanize

Humanize Skill

This skill only removes AI patterns; it does not perform general copy-editing, evaluate scientific quality, check journal formatting, or translate.

Read ${CLAUDE_SKILL_DIR}/references/ai_patterns.md at the start of every session, before scanning: the definitions, watch words, examples, detection greps, per-pattern fixes and the section-by-section priorities for all 27 patterns live only there.

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Workflow

Phase 1: Scan

Scan the section(s) the user provides for all 27 patterns. For response-to-reviewers letters and cover letters, prioritise Patterns 22-24. For a full manuscript, follow the per-section priorities in ai_patterns.md (Section-Specific Application Guide). For each pattern found, record its number and name, the count, the exact passage, and its location (paragraph number or line range).

Output: Pattern Frequency Table

## AI Pattern Scan Report

Section: {section name}
Word count: {N}

| # | Pattern | Count | Severity | Example from text |
|---|---------|-------|----------|-------------------|
| 1 | Significance inflation | 3 | HIGH | "...pivotal role in diagnostic imaging..." |
| ... | ... | ... | ... | ... |

Patterns not detected: 2, 4, 9, 14, 15

Total AI pattern instances: {N}
AI pattern density: {N per 1000 words}

Phase 2: Report

• Severity per pattern: HIGH (>3 occurrences), MEDIUM (1-3), LOW (0, clean).
• Density: total instances across all 27 patterns per 1000 words. Target: < 2.0.

Gate: Present the report and ask the user which patterns to fix. Default: fix all HIGH and MEDIUM.

Phase 3: Fix

Rewrite flagged passages with each pattern's fix from ai_patterns.md, under these rules:

1. Preserve technical accuracy. Every number, statistic, p-value, confidence interval, and clinical fact must remain identical.
2. Preserve citations. Never add, remove, or relocate a citation.
3. Keep the formal academic register of an experienced radiologist writing for peers in a top-tier journal. Never make the text casual or conversational.
4. Keep domain-specific terminology intact. "Convolutional neural network," "apparent diffusion coefficient," "Fleiss' kappa" stay as-is.
5. Never introduce new claims, remove existing ones, or change a sentence's meaning — rephrase, never reinterpret. If a passage cannot be fixed without changing its meaning, leave it and flag it for the user.
6. Use active voice where natural: "We analyzed" rather than "Analysis was performed."
7. Vary sentence structure. Mix short declarative sentences (8-12 words) with longer ones (25-35 words). A de-AI pass tends to flatten rhythm — it shortens the long sentences and pads the short ones toward a comfortable middle, which is itself a tell. scripts/check_sentence_variety.py verifies this rule in Phase 4.
8. Thin out antithesis and cleft constructions (Pattern 27, the M2 heuristic). For each "X rather than Y", "not X but Y" or "X, not Y", apply the negative-form test: delete the negative half and rewrite the clause in the positive. If a fact disappears, the contrast was functional — keep it; if nothing disappears, it was decoration — cut it. Judge by the manuscript's overall rate, not instance by instance, and keep two or three for emphasis. Rewrite clefts ("What … is …", "It is … that …") in plain subject-verb order ("What matters is X" → "X matters"). scripts/check_rhetorical_density.py (in /self-review) measures this in Phase 4.