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.
npx skills add ApurvBazari/claude-plugins --skill doc-auditgit clone --depth 1 https://github.com/ApurvBazari/claude-pluginsWrote 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.
[](https://agentmods.dev/skills/apurvbazari/claude-plugins/doc-audit)<a href="https://agentmods.dev/skills/apurvbazari/claude-plugins/doc-audit"><img src="https://agentmods.dev/badge/skills/apurvbazari/claude-plugins/doc-audit/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.
<a href="https://agentmods.dev/skills/apurvbazari/claude-plugins/doc-audit"><img src="https://agentmods.dev/badge/skills/apurvbazari/claude-plugins/doc-audit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00081 | $0.00860 |
| Opus 5.5 | $0.00032 | $0.00344 |
| Sonnet 5.5 | $0.00016 | $0.00172 |
| Haiku 4.5 | $0.00008 | $0.00086 |
Grade A, and why
doc-audit 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 22d 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.
How it starts
The opening of the file, as written. The whole thing — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/doc-audit — Documentation Completeness Auditor & Fixer
Audit the marketplace's docs against machine truth (SKILL.md frontmatter + manifests), then
surgically fix the mechanical gaps and flag the rest. Read-only detection lives in
audit-docs.sh; the edits below are applied by you, the model, only on the fix pass.
Guard
This skill edits files (READMEs). It is user-invoked only. On a real run it will modify
plugin READMEs and the root README in the working tree — the user reviews via git diff.
Never run the fix pass outside a git working tree where changes can be reviewed/reverted.
Step 1: Detect
Run the audit and read the full report:
bash .claude/skills/doc-audit/scripts/audit-docs.sh --format pretty
(Optionally --root <dir> to audit a different checkout, e.g. a worktree.)
Step 2: Present the report
Summarise the findings grouped by severity (ERROR / WARN / INFO) and by layer. Include the coverage table (command → documented?) so the user sees included-vs-omitted without asking.
Step 3: Surgical fix pass (auto-fixable findings only)
Read references/completeness-contract.md for the exact rules and scaffold shape. Then, for each
auto-fixable finding, make the smallest edit that resolves it:
MISSING_SKILLS_SECTION→ add a## Skillssection scaffolded from frontmatter.CMD_NOT_IN_README→ insert one entry (scaffold shape) in canonical order.MARKER_MISSING→ add*(destructive — user-invoked only)*to that entry's header only.PLUGIN_NOT_IN_ROOT→ add the plugin to the root "at a glance" table and command index.ROOT_COUNT_STALE→ correct the plugin-count word/number.ROOT_NO_CMD_INDEX→ add a central command index listing every plugin's user commands. If a command section already exists, extend it in place — never add a second index (the fix is idempotent: re-running must produce no further change).
Surgical rule: never rewrite an existing hand-written entry. Only add what is missing or correct a marker/count. Preserve tables, prose, and ordering already present.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 22d ago Changed 60218251d5ef
- 1mo ago First seen · 73 lines · 81 tokens per session scan A 43b87cb1c74b
doc-audit is a skill published in the GitHub repository ApurvBazari/claude-plugins (3 stars, last pushed 3d ago), licensed MIT. It adds 81 tokens to every session and 860 once invoked, about $0.0003 per session on Opus 5.5. 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.
Other skills, from other repositories
c-notify
Send native macOS notification center alerts from the command line using terminal-notifier.
notifications
Send notifications through the unified notification router.
telegram-setup
Connect a Telegram bot to the Vellum Assistant gateway with automated webhook registration and credential storage.
test-warp-ui
Guides testing Warp UI features and changes using the computer use tool. Use this skill only when computer-use testing was requested (explicit request or accepted offer) and the computeruse tool is available to the agent. Covers launching Warp and verifying UI behavior.
agenticx-query-data-source
Use when the user asks about verifiable quantitative facts (stock prices, financial indicators, macro data, company registry, academic metrics, legal statutes) that must come from a live data source rather than training memory.
start-the-day
An on-demand personal daily briefing — weather, headlines, the shape of your day, and one thing worth your attention — in a sharp executive-assistant voice. The general-purpose morning brief; richer work or admin digests compose it as their general layer.