doc-auditor

doc-auditor is an agent for Claude Code from Mexregkan/claude-for-researchers. It costs 114 tokens per session (1,395 once invoked), scanned A, original, MIT.

A read-only reviewer for checking one claim in a project document against the document and its cited evidence. It reports whether the wording is supported or makes a stronger claim than the evidence allows.

In plain words
What is it for?
It helps audit claims by reading the relevant passage, scripts, logs, outputs, and related records without changing any files.
Why use it?
It helps catch inaccurate statements before they are reused in plans, reports, or later project sessions.

Agent for Claude Code

Written for Claude Code: installed under .claude/. Also seen: model in frontmatter; mentions CLAUDE.md.

Good fit It helps audit claims by reading the relevant passage, scripts, logs, outputs, and related records without changing any files.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/mexregkan/claude-for-researchers/doc-auditor
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Clone the repo
git clone --depth 1 https://github.com/Mexregkan/claude-for-researchers

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for doc-auditor

README.md
[![agentmods](https://agentmods.dev/badge/agents/mexregkan/claude-for-researchers/doc-auditor/github.svg)](https://agentmods.dev/agents/mexregkan/claude-for-researchers/doc-auditor)
Your own site
<a href="https://agentmods.dev/agents/mexregkan/claude-for-researchers/doc-auditor"><img src="https://agentmods.dev/badge/agents/mexregkan/claude-for-researchers/doc-auditor/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for doc-auditor

Your own site · 80×15
<a href="https://agentmods.dev/agents/mexregkan/claude-for-researchers/doc-auditor"><img src="https://agentmods.dev/badge/agents/mexregkan/claude-for-researchers/doc-auditor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 114 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,395 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00114 $0.01395
Opus 5 $0.00057 $0.00698
Sonnet 5 $0.00023 $0.00279
Haiku 4.5 $0.00011 $0.00139

Measured 6d ago against content hash 06ecdfc93751, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

doc-auditor scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

starter/.claude/agents/doc-auditor.md · 88 lines

How it starts

The opening of the file, as written. The whole thing — 88 lines — stays where its author put it; the contents beside it link to each section on GitHub.

doc-auditor

You audit one claim of one document. Your job is not to re-audit the document: it is to find out whether this statement, as written, is safe to rely on. You are read-only — you REPORT; you never edit the document, a record, a script or a log, and you never start a long computation.

The asymmetry that defines the role: a wrong SUPPORTED lets a false statement propagate into the strategy map, the next session and the paper; a wrong OVERCLAIMED costs a round and erodes trust in the audit. Attack both, and hardest the one the caller is about to rely on.

Inputs you will be given

The bare claim as a sentence; file:lines; the path to the definitions or conventions it needs; the evidence paths (script, log, output, handoff id, CHANGELOG row) if the document names any. You will not be given the caller's verdict, ledger or story. If any of those reach you anyway, say so at the top of your report — the fresh read is worth less.

Method

  1. Read the passage yourself, from the file, the stated lines plus enough context to see the paragraph's own typing. Check the claim you were handed against the text word for word. A mis-stated claim is the most common defect and the most damaging: if the document says something weaker or different, say so first. (The claim you were handed should be a quote from the document, not a sibling record's paraphrase of it. If it reads like a paraphrase, say so.)
  2. Read the evidence, then run the cheap checks.
    • A script: find the check whose body tests the claim. Write the weakest statement that makes that body pass (claim-audit step 2). Does the label say more than the body? Is the object hand-assigned upstream? Would the body pass for an arbitrary object of the same type?
    • A log: count the things the prose asserts about it — pass lines, abort lines, error and warning lines, and the completion sentinel on the last line — and compare with what the document says. A clean process exit is not a pass.
    • An output or data file: does it exist, is it tracked (git ls-files --error-unmatch), is it the version the document's date implies?
    • A derivation in the text: is every step reversible from the stated inputs, or does one step land on the answer? Look for "one finds", "a short computation", and for the moment an expression suddenly matches the conclusion.
  3. Check the sibling records. Grep a distinctive constant, phrase or script name from the claim in strategy-map.md, CHANGELOG.md, bigPicture.tex, brief.tex, CLAUDE.md, handoff/msgs/ and handoff/archive/. Same strength? Same list of conditions? Same numbers? Quote both sides of any disagreement. Do not treat any of them as ground truth — they are co-claims.
  4. Attack the conventions. Check the claim against CLAUDE.md § Conventions. The model failure: a bound imported from another source with its normalisation one factor off, then inherited by every downstream record. Nothing errors; the number is wrong everywhere at once.
  5. Hunt the unstated assumption. For the claim to hold, what had to be true that nobody wrote down — a frozen input, a chosen branch, a limit order, a leading-order truncation, an accepted correction restated stronger than the corrector made it? Name each.
  6. Verify before asserting. Run the grep, read the lines, count the checks. "I ran X and got Y" beats "X looks wrong". A plausible but unverified objection costs the next session a full round trip.

Read the full file on GitHub · 88 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 6d ago First seen · 88 lines · 114 tokens per session scan A 06ecdfc93751

Subscribe to this mod's changes

doc-auditor is an agent published in the GitHub repository Mexregkan/claude-for-researchers (52 stars, last pushed 7d ago), licensed MIT. It adds 114 tokens to every session and 1,395 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-05.

Related

Other agents, from other repositories

claim-verify

Verify that cited claims in a paper accurately represent what the source papers actually say. Checks every factual claim against its reference. Read-only with respect to project files (paper, bib, cited PDFs); writes its own Claim Verify Report and typed citation-integrity component at reviews/ /claim-verify/ ..…

flonat/flonat-research · 391 tokens

peer-reviewer

Use this agent when you need to review someone else's paper — as a peer reviewer, discussant, or for reading group preparation. This agent reads the PDF carefully using split-pdf methodology, spawns parallel sub-agents for citation validation, novelty assessment, and methodology review, scans for hidden prompt…

flonat/flonat-research · 352 tokens

code-review

Multi-persona orchestrator for adversarial review of R, Python, Julia, or Stata research scripts. Runs an 11-category baseline checklist, then dispatches 3-6 specialist sub-agents (correctness, reproducibility, design, plus optional domain / performance / security) in parallel. Deduplicates findings across reviewers…

flonat/flonat-research · 398 tokens

fatal-error-check

Fast pre-review check for fatal errors in LaTeX papers. Launch BEFORE full review agents (paper-critic, domain-reviewer, referee2-reviewer). Binary PASS/FAIL verdict in 15-30 seconds. Checks compilation, placeholders, broken references, number contradictions, and section completeness. Examples: Example 1: user: "Quick…

flonat/flonat-research · 180 tokens

skill-creator

Generates or modifies optimized skill files. In creation mode, builds from raw user knowledge. In modification mode, applies targeted changes to existing skills while preserving unchanged content. Use when creating new skills or updating existing ones.

shinpr/rashomon · 47 tokens

skill-eval-reporter

Compares repeated paired execution results using blind A/B methodology and generates a skill effectiveness report. Use when valid skill-evaluation result pairs are available.

shinpr/rashomon · 35 tokens