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Whitepaper Audit Agent Skill

Audit a white paper or long-form technical document against a research-grounded best-practices checklist. Two lanes — deterministic script checks (readability, undefined acronyms, structure blocks, broken links) plus an LLM-judge review (overclaims, inconsistent numbers, buried lede, limitations honesty, audience fit). Produces a prioritized P0–P2 findings report by default; applies fixes on explicit request (TDD for any code changes). Use when the user says "audit this white paper", "review my paper against best practices", "check this doc for overclaims", "whitepaper QA", "is this paper ready to publish", or wants prioritized recommendations on a technical document.

13k tokens
context cost
the whole folder, loaded on every use
14
files
ships runnable scripts
0
copies elsewhere
how many repositories repackaged it
337
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/glebis/claude-skills --skill whitepaper-audit

What comes with it

48 507 bytes besides the instruction
DESIGN.md
evals/README.md
evals/RESULTS.md
evals/cases/clean-control.md
evals/cases/missing-limitations.md
evals/cases/planted-defects.md
evals/stripped/clean-control.md
evals/stripped/missing-limitations.md
evals/stripped/planted-defects.md
references/audit-prompt.md
references/checklist.md
scripts/check_doc.py
scripts/tests/test_check_doc.py

What it tells the agent to use

found in the instruction text
Task spawns other agents

The instruction itself

10 sections, as written by the author

whitepaper-audit

Audit a markdown white paper in two lanes and produce one merged, prioritized report.

Inputs

  • Document path (required) — markdown source, not PDF.
  • Stated audience (ask if not given) — severity of audience-fit/jargon-undefined

depends on it. Default: "technical practitioners, non-academic".

  • Moderecommend (default) or fix (only on explicit request).

Workflow

1. Lane 1 — deterministic

python3 scripts/check_doc.py <doc.md> --offline [--target-grade N] [--allow ACRO]

Drop --offline to also check http(s) links (HEAD→GET, timeouts; only *broken* is a

finding). Output: JSON findings, schema in DESIGN.md.

2. Lane 2 — LLM judge

Dispatch a subagent (fresh context — never judge a document you wrote in the same

context) with references/audit-prompt.md, filling {PATH} and {AUDIENCE}, plus the

[judge] criteria from references/checklist.md. The judge returns JSON findings.

Judge calibration rules are binding: verbatim quotes required; no P0 at low confidence;

"needs verification", never "factually wrong".

3. Merge

Dedupe by (location, issue type) keeping both lane attributions; sort P0 → P1 → P2, then

confidence. Cross-reference: a lane-1 broken link that supports a claim (judge decides

materiality) is P1; decorative → P2.

4. Report (default mode)

Write a markdown report: summary verdict, findings table (id, severity, confidence,

location, fix), then details. Recommend; do not edit.

5. Fix mode (only when explicitly requested)

Apply fixes P0-first. Any change to code goes through superpowers

test-driven-development (test first, watch it fail). Prose fixes: edit, then **re-run the

full audit** and report cleared vs remaining findings.

Evals

Before trusting a new/changed judge prompt, run evals/README.md procedure (planted

defects + clean control; pass criteria inside). Lane 1 is covered by

scripts/tests/test_check_doc.py (pytest).

Files

  • scripts/check_doc.py — lane 1 (stdlib-only; --help for flags)
  • references/checklist.md — operational criteria, both lanes
  • references/audit-prompt.md — judge prompt template
  • evals/ — judge validation cases + pass criteria
  • DESIGN.md — architecture decisions (v0.2, Codex-audited)

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How to use it

Copy the folder

Take glebis/whitepaper-audit from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.