review

review is a skill for Claude Code from TheWinci/mimirs. It costs 60 tokens per session (369 once invoked), scanned A, original, Apache-2.0.

A remote MCP server that provides structured, token-efficient data from YouTube. MCP is a way for an AI application to connect to external tools and data sources.

In plain words
What is it for?
Use it when an LLM application needs to access or process YouTube data.
Why use it?
It gives an AI application organized YouTube information to use in its responses or other workflows.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the mimirs plugin — 11 skills, 3 hooks shipped together

Good fit Use it when an LLM application needs to access or process YouTube data.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/thewinci/mimirs/review
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.

Any agent
npx skills add TheWinci/mimirs --skill review
Clone the repo
git clone --depth 1 https://github.com/TheWinci/mimirs

Made for: Claude Code.

Or install mimirs, the plugin that ships this one along with the rest of its 11 skills, 3 hooks.

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

README.md
[![agentmods](https://agentmods.dev/badge/skills/thewinci/mimirs/review.svg)](https://agentmods.dev/skills/thewinci/mimirs/review)
Your own site
<a href="https://agentmods.dev/skills/thewinci/mimirs/review"><img src="https://agentmods.dev/badge/skills/thewinci/mimirs/review.svg" alt="Measured on agentmods" height="20"></a>
Per session 60 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 369 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 $0.00060 $0.00369
Opus 5 $0.00030 $0.00185
Sonnet 5 $0.00012 $0.00074
Haiku 4.5 $0.00006 $0.00037

Measured 8d ago against content hash c0902d2ddd2b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

review 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 8d 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.

skills/review/SKILL.md · 18 lines

What it actually says

Review

Goal: know the full impact before and after changing code — no surprise breakage.

  1. What changedgit_context(include_diff: true) for the modified files and the diff.
  2. Blast radius — for each changed function or type: impact <symbol> (transitive callers as a pruned tree + the tests to run). Widen with usages <symbol> (every call site) and dependents <file> (file-level importers). Pass file to impact to disambiguate a name defined in several places.
  3. Tests to runaffected for the changed set (CLI: git diff --name-only | mimirs affected --stdin). Run those before claiming the change is done.
  4. Known caveatsget_annotations on the touched files: fragile code, constraints, "don't refactor until X".
  5. Why it's like thissearch_checkpoints "<area>" (prior decisions) and search_commits "<area>" (why it changed before), so you don't undo a deliberate choice.
  6. After the change — re-run impact / affected; annotate any new caveat you introduce; create_checkpoint the decision and what changed.

Finish: a risk summary — callers affected, tests to run, caveats, prior decisions — each with a file:line citation.

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. 8d ago First seen · 18 lines · 60 tokens per session scan A c0902d2ddd2b

Subscribe to this mod's changes

review is a skill published in the GitHub repository TheWinci/mimirs (29 stars, last pushed 24d ago), licensed Apache-2.0. It adds 60 tokens to every session and 369 once invoked, about $0.0003 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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