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paper-spine-humanize

paper-spine-humanize

github.com/wubing2023Documents6.1k243 installsUpdated 2w ago
Repository

About paper-spine-humanize

A standalone or PaperSpine-integrated skill for revising academic text with tier-specific writing constraints. It records each change in a teaching matrix and checks coverage and writing patterns.

Key features

  1. 01Applies configurable humanization tiers
  2. 02Records changes in a matrix
  3. 03Checks sentence and paragraph patterns
  4. 04Supports Chinese and English output

Use cases

  1. 01Revising academic text standalone
  2. 02Applying configured constraints in PaperSpine
  3. 03Documenting edits for writing instruction

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/wubing2023/paperspine --skill paper-spine-humanize

After installing, type/paper-spine-humanizein Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

agents/
openai.yaml
references/
humanize-tiers-en.md
humanize-tiers-zh.md
platform-cnki.md
platform-general.md
platform-weipu.md
scripts/
humanize_check.py

Details

From the project README

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 IDManuscript UnitAI Pattern FoundDetection DimSeverityApplied ChangeExpected EffectTeaching 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.

Comments

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