paper-spine-humanize

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_tier is not none
• 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.