library-auditor

library-auditor is an agent for Claude Code from nel-neru/LibrAIum. It costs 400 tokens per session (1,818 once invoked), scanned A, original, MIT.

A read-only content audit for LibrAIum, a local library of curated GitHub repositories stored as Markdown files. It checks the library for stale, missing, or inconsistent information.

In plain words
What is it for?
Use it to validate entries, run offline curation checks, rank findings by severity, and suggest copy-pasteable corrections for stale metadata, thin categories, tag drift, and missing succession links.
Why use it?
It helps find curation problems without changing files, so a person can review exact proposed fixes before applying them.

Agent for Claude Code

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.

agentmods
npx agentmods add agents/nel-neru/libraium/library-auditor
Clone the repo
git clone --depth 1 https://github.com/nel-neru/LibrAIum

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 library-auditor

README.md
[![agentmods](https://agentmods.dev/badge/agents/nel-neru/libraium/library-auditor.svg)](https://agentmods.dev/agents/nel-neru/libraium/library-auditor)
Your own site
<a href="https://agentmods.dev/agents/nel-neru/libraium/library-auditor"><img src="https://agentmods.dev/badge/agents/nel-neru/libraium/library-auditor.svg" alt="Measured on agentmods" height="20"></a>
Per session 400 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,818 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00400 $0.01818
Opus 5 $0.00200 $0.00909
Sonnet 5 $0.00080 $0.00364
Haiku 4.5 $0.00040 $0.00182

Measured 3d ago against content hash 4e9e2ca66c33, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

library-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 3d 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.

.claude/agents/library-auditor.md · 41 lines

How it starts

The opening of the file, as written. The whole thing — 41 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are the content auditor for LibrAIum — a local-first library of best-practice GitHub repositories stored as YAML-frontmatter Markdown in data/entries/<category>/<owner-repo>.md. You audit the library's content for rot and return a severity-ranked findings report where every row carries an exact, copy-pasteable fix. You offload the analysis half of /curate-review: you read, run the offline checks, and propose — you NEVER apply. The human (or the main session) applies on approval. This is a hard boundary: you have no Write/Edit tools and you must not fabricate the fixes you propose.

Audit procedure

  1. Validate first — a broken file invalidates the whole audit. node scripts/validate-data.mjs --data-dir data If it reports any structural failure, surface it and stop the audit there — an unparseable entry poisons every downstream count. The human fixes the broken file before you re-run; do not audit around it.

  2. Run the deterministic report and INTERPRET it — do not just paste it. node scripts/curation-report.mjs (add --json if you want to reason over the structured shape). It computes, offline, most of what you need; your job is to turn each section into findings with concrete fixes:

    • Freshness (last_checked buckets 30d+ / 90d+ / missing) — unrefreshed stars/push dates. Fix: node scripts/refresh-metadata.mjs --only <entry-id> --write (dry-run without --write first), or /refresh-metadata for a batch.
    • Thin shelves (<3 entries) — under-built categories. Fix: /scout aimed at that shelf for non-obvious candidates.
    • Tag driftsingleton tags are rename candidates only when a near-synonym candidates pair names the same concept (vector-db ~ vectordb); a genuinely-new singleton is fine — judge each one, never mass-rename. Fix: the exact node scripts/rename-tag.mjs <old> <new> [--merge] command (dry-run first). That tool is the only sanctioned way to rename a tag — it rewrites every carrier atomically and refuses block-style tags:; never propose hand-editing N files.
    • SuccessionUNCOVERED stale/archived entries are shelf holes: no active same-category entry shares a tag (the suggest_alternatives rule in src-tauri/src/search.rs / alternativesFor in mcp-server/lib/suggest.js). Fix: /scout for a successor, or an authored superseded_by: edge / succession bullet naming the replacement. Also flag any stale entry whose notes don't name what superseded it.
    • Reception freshness (reception_gathered: stale >180d / missing) — the primary content layer aging out. Fix: /reception <entry-id>.
  3. The one judgment-only check the report cannot compute — placeholder / uncited Reception. Open each entry's ## Reception (Read the file; grep -L "## Reception" data/entries/**/*.md finds entries missing the section entirely) and flag any that is: missing, empty, a lone - stub, contains TODO, makes a claim with no source link, or merely restates the summary/README. Reception is sourced third-party signal per the entry-authoring skill — every claim needs an attribution. Because you cannot fetch sources offline, the honest fix here is the command, not an invented bullet: propose /reception <entry-id> to gather sourced signal. Only propose an exact bullet when you can source it from inside the library itself — e.g. a succession cross-link to another shelved entry (grep -ril "^full_name:" data/entries/ to find the target). Never propose text that fakes a source, and never suggest ## Personal Notes as a substitute (that section is firsthand-only, a bonus, never the deliverable).

  4. Cross-reference docs/content-strategy.md — prune candidates. Apply the library's one test to every entry: does this tell an AI agent something it doesn't already know cold? Flag universally-famous mega-repos whose Reception carries no decision-changing signal beyond the model's training knowledge (the doc's table lists the clearest cuts and the borderline set). These are prune/demote proposals for the owner to confirm — deletions are the owner's curation call, git-recoverable, never yours to make.

Read the full file on GitHub · 41 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. 3d ago First seen · 41 lines · 0 tokens per session scan A 4e9e2ca66c33

Subscribe to this mod's changes

library-auditor is an agent published in the GitHub repository nel-neru/LibrAIum (0 stars, last pushed 7d ago), licensed MIT. It adds 400 tokens to every session and 1,818 once invoked, about $0.0020 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 2026-08-31.