TMDb: Skill for Claude Code

.claude/skills/review-knowledge/SKILL.md

review-knowledge is a skill for Claude Code from adamayoung/TMDb. It costs 113 tokens per session (5,825 once invoked), scanned A, original, Apache-2.0.

An audit of the project's knowledge files and agent instructions against the current code and configuration. It uses four independent checks to find outdated claims, contradictions, and differences between the documented rules and the repository.

In plain words
What is it for?
Use it to check the knowledge base and the .claude directory for stale or conflicting information. It is useful after changes to build files, workflows, package settings, tools, or project structure.
Why use it?
Documentation and agent instructions can become wrong as the code changes, even when they still sound confident. This audit verifies important claims against the files that actually exist.

Skill for Claude Code

Written for Claude Code: installed under .claude/. Also seen: reads .claude/ paths; mentions CLAUDE.md.

This is adamayoung/TMDb's own configuration. It tells Claude Code how to work on TMDb itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything TMDb configures →

Reuse

Borrowing it

Nothing to install: this file belongs to adamayoung/TMDb. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/adamayoung/TMDb/main/.claude/skills/review-knowledge/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/adamayoung/TMDb

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 review-knowledge

README.md
[![agentmods](https://agentmods.dev/badge/skills/adamayoung/tmdb/review-knowledge/github.svg)](https://agentmods.dev/skills/adamayoung/tmdb/review-knowledge)
Your own site
<a href="https://agentmods.dev/skills/adamayoung/tmdb/review-knowledge"><img src="https://agentmods.dev/badge/skills/adamayoung/tmdb/review-knowledge/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 review-knowledge

Your own site · 80×15
<a href="https://agentmods.dev/skills/adamayoung/tmdb/review-knowledge"><img src="https://agentmods.dev/badge/skills/adamayoung/tmdb/review-knowledge.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 113 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 5,825 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00113 $0.05825
Opus 5 $0.00056 $0.02913
Sonnet 5 $0.00023 $0.01165
Haiku 4.5 $0.00011 $0.00583

Measured 10d ago against content hash ea613ba8db0b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

review-knowledge 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 10d 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/skills/review-knowledge/SKILL.md · 342 lines

How it starts

The opening of the file, as written. The whole thing — 342 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Review Knowledge

Audit knowledge/ and .claude/ against reality. Both are a cache of currently-true facts (knowledge/README.mdMaintenance & retention), and caches go stale silently: writes are engineered here (/capture-knowledge, /deliver's capture phase) but retirements are not, so truth decays exactly where the code moves fastest — Makefile, .github/workflows/ci.yml, Package.swift, target layout, toolchain pins.

Four independent adversarial auditors — an accuracy lens and a structure lens over each of the two trees — audit them, cross-examine each other's findings within their tree, and converge on a consensus. You adjudicate only what survives disputed.

The base's own entries are the thing under suspicion. An entry that reads confidently and cites a file is exactly the kind that goes stale unnoticed — confidence is not currency here. Verify against the tree or drop the claim.

Agent Behaviour Contract

The point of this skill: do these by default, without being reminded.

  1. Two lenses × two trees, one Workflow. Run the embedded Workflow below. It fans out four auditors in parallel — each lens against each tree — every one pinned to the opus model, then runs a cross-examination round paired within each tree, so the two lenses challenge each other on the same material. Invoking this skill is itself the opt-in to call Workflow. A tree whose pair doesn't both return is reported unreconciled, never as consensus. The cross-examination stays on fable — do not unify the two tiers. The rounds are not symmetric: a refutation is written to the permanent refutation memory (item 2) and silently suppresses that finding on every later audit, so a weak refuter costs far more than a weak auditor. An audit miss, by contrast, is re-derivable next run. See ADR-0020.
  2. Consult the refutation memory first. Before reporting, grep knowledge/skill-improvement-log.md for · refuted entries and drop any finding already settled there whose Reconsider when condition is unmet. Say in the report how many you dropped this way. Re-deriving a settled refutation costs a full audit cycle and buys nothing.
  3. Verify, never trust the prose. Every finding must be checked against the actual tree (Read/Grep/Bash) and cite file:line. A finding sourced only from reading the knowledge base itself is inadmissible — that is the failure mode being audited.
  4. Critics are read-only. They audit and report. They do not edit knowledge/, do not fix anything, and do not open PRs. Applying is the conductor's job, after the user approves.
  5. "Nothing needs changing" is a real, respectable outcome. A critic that finds a file accurate must say so and name what it checked. Do not manufacture findings to look thorough — a padded audit trains the next one to be ignored.
  6. Adjudicate only genuine deadlock. After cross-examination, findings both critics confirm are consensus and need no debate from you. Resolve only what remains disputed, with a stated rationale grounded in the tree.
  7. Report before you fix. Present the consensus, get the user's go-ahead, then apply. Never silently rewrite the knowledge base on the strength of an audit.

Read the full file on GitHub · 342 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. 10d ago First seen · 342 lines · 113 tokens per session scan A ea613ba8db0b

Subscribe to this mod's changes

review-knowledge is a skill published in the GitHub repository adamayoung/TMDb (176 stars, last pushed 9d ago), licensed Apache-2.0. It adds 113 tokens to every session and 5,825 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 2026-08-30.

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