By name: paper-spine-humanize description: Reduces AI detection rates via tiered stylistic constraints mapped to real AIGC detection dimensions. Produces a teaching humanize_matrix.md. (internal /paperspine step)
PaperSpine Humanize
Self-contained skill — can be used standalone on any academic text, or as part of the PaperSpine suite. Applies tier-specific writing constraints based on real AIGC detection dimensions and produces a teaching matrix that documents every change.
When To Use
- In PaperSpine: auto-invoked by rewrite/build when
humanize_tieris notnone - Standalone: invoke directly on any academic text that needs AI detection reduction
Configuration
Read paper_spine_config.json for humanize_tier (none/light/medium/heavy)
and output_language (zh/en). When used standalone, default to medium / zh
if no config found.
Required Output: humanize_matrix.md
This is the primary deliverable — produce paper_rewriting_output/humanize_matrix.md.
Every humanization change must be recorded, not applied silently:
| Row ID | Manuscript Unit | AI Pattern Found | Detection Dim | Severity | Applied Change | Expected Effect | Teaching Note |
|---|
- Manuscript Unit: paragraph number or section name
- AI Pattern Found: specific AI feature detected
- Detection Dim: D1-D5 (see reference document)
- Severity: High (>50% contribution to detection) / Medium (20-50%) / Low (<20%)
- Applied Change: what specific change was made
- Expected Effect: which dimension this reduces
- Teaching Note: why detectors flag this pattern
Matrix Rules
- Write rows during writing, one per unit processed — not after the fact
- At least one row per writing unit for D1 (sentence length)
- At least one row per paragraph for D2 (paragraph structure)
- At least one row per connector replaced (D4)
- At least one row per density adjustment (D3, medium+)
- At least one row per term substitution (D5, heavy only)
- Fill all 8 columns for every row — no empty cells
Instructions
Read references/humanize-tiers-{output_language}.md for the complete
tier-specific directives mapped to the 5 detection dimensions:
D1-Sentence Length / D2-Paragraph Structure / D3-Information Density /
D4-Connector Frequency / D5-Term-Context Matching.
Verification
python scripts/humanize_check.py paper_rewriting_output --markdown --write
Produces paper_rewriting_output/humanize_report.md. Checks matrix coverage
against total paragraphs, scans sentence-length distribution and connector
density, and flags remaining AI patterns.
Integration
In PaperSpine: called internally by rewrite and build. Standalone: place this
skill directory under ~/.claude/skills/ and invoke directly.