AugmentClaude

Paper Format Agent

Inspect, score, and repair academic paper formatting in DOCX files.

Installation

  1. Make sure Claude is on your device and in your terminal.

    Skills load from ~/.claude/skills/ when Claude Code starts up — so you need it on your machine first. If you don't have it yet, install it once with the command below, then run claude in any terminal to verify.

    One-time setup
    npm i -g @anthropic-ai/claude-code

    Already have it? Skip ahead.

  2. Paste into Claude Code or into your terminal.

    This copies the whole skill folder into ~/.claude/skills/paper-format-agent-zxyasfas/ — the SKILL.md plus any scripts, reference docs, or templates the skill ships with. Safe default: works for every skill.

    Faster alternative (instruction-only skills)

    Skips the clone and grabs only the SKILL.md file. Don't use this if the skill ships Python scripts, reference markdowns, or asset templates — they won't be downloaded and the skill will fail when it tries to load them.

    Quick install (SKILL.md only)
    Sign up to copy
  3. Restart Claude Code.

    Quit and reopen Claude Code (or any other agent that loads from ~/.claude/skills/). New skills are picked up on startup.

  4. Just ask Claude.

    Skills auto-activate when your request matches the skill's description — no slash command needed. Trigger phrases live in the skill's own frontmatter; you can read them in the “What this skill does” section above.

Prefer to read the source first? Open on GitHub.

When Claude uses it

Use this skill when a user needs to inspect, score, repair, or regression-test academic paper formatting in DOCX files, especially thesis, journal, or conference documents with a separate format specification. The skill guides Codex through local-first document handling, rule extraction, formatting repair, report review, and contribution-safe validation.

What this skill does

Paper Format Agent

Use this skill for local-first academic document formatting work. It is designed for .docx papers and a separate format specification in .docx, .doc, or .txt.

Safety Defaults

  • Never upload private papers or format guides to external services unless the user explicitly asks for it.
  • Treat student papers, manuscripts, reviewer comments, and school templates as sensitive data.
  • Do not change academic content unless the user explicitly opts in. Default to formatting-only changes.
  • Keep reports and generated documents in a user-provided output directory.

Standard Workflow

  1. Confirm the input files:
    • --format-file: format guide or template text.
    • --paper-file: source paper, currently .docx.
    • --out-dir: output directory for reports and generated documents.
  2. Run the CLI in formatting-only mode:
python -m paper_format_agent.cli \
  --format-file "format_guide.docx" \
  --paper-file "paper.docx" \
  --out-dir "./output" \
  --engine auto \
  --strict-required-sections
  1. Inspect generated artifacts:
    • formatted_paper_v3.docx: repaired document.
    • format_rules.json: extracted rules.
    • format_report.json: machine-readable score and checks.
    • format_report.html: human-readable report.
    • modify_log.json: formatting operations.
    • engine_report.json: post-processing engine result.
  2. Check the content guard fields in format_report.json:
    • content_changed should normally be false.
    • content_guard_enforced should normally be true.
  3. If a rule is wrong, update rule extraction or scoring logic and add a minimal test case.

Validation

Run these before handing work back:

python tools/validate_skill.py
python -m unittest discover -s tests -p "test_*.py"
python tools/compile_check.py
python tools/release_audit.py

When Adding Template Support

  • Add the smallest representative rule text needed to reproduce the behavior.
  • Prefer deterministic rule extraction over LLM-only interpretation.
  • Add tests for extracted margins, font size, line spacing, required sections, headings, captions, or references.
  • Do not commit real student documents. Use synthetic text or anonymized fixtures.

When Reviewing Output

Read format_report.json first, then inspect format_report.html if the user needs a human-readable summary. Prioritize issues in this order:

  1. Content changed unexpectedly.
  2. Required sections or headings were misclassified.
  3. Page setup, margins, fonts, or line spacing are wrong.
  4. Captions, references, tables, or numbering look wrong.
  5. Report wording or score explanation is unclear.

Contribution-Friendly Tasks

Good first PRs usually fit one of these buckets:

  • Add a synthetic test for a school, journal, or conference formatting rule.
  • Improve a rule extractor with a narrowly scoped regex or parser.
  • Improve report clarity without changing scoring semantics.
  • Add a regression case to docs/regression_manifest.sample.json.
  • Improve this skill workflow or agents/openai.yaml metadata.

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