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 kimon1230/claude_extensions --skill code-reviewgit clone --depth 1 https://github.com/kimon1230/claude_extensionsWrote 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/kimon1230/claude_extensions/code-review)<a href="https://agentmods.dev/skills/kimon1230/claude_extensions/code-review"><img src="https://agentmods.dev/badge/skills/kimon1230/claude_extensions/code-review/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/kimon1230/claude_extensions/code-review"><img src="https://agentmods.dev/badge/skills/kimon1230/claude_extensions/code-review.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 | $0.00041 | $0.03945 |
| Opus 5.5 | $0.00016 | $0.01578 |
| Sonnet 5.5 | $0.00008 | $0.00789 |
| Haiku 4.5 | $0.00004 | $0.00394 |
Grade A, and why
code-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 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.
How it starts
The opening of the file, as written. The whole thing — 189 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Review
This skill must only be invoked from the main session, never from a subagent.
1. Determine Scope
a. If the user specified file paths, directories, or a description of what to review, use that as the scope.
b. If the user said "review my changes" or similar, use git diff HEAD (unstaged + staged) and git diff --cached as the scope. Include full file context for changed functions, not just the diff hunks. If no changes exist, tell the user and stop.
c. If no scope is specified, ask the user: "What should I review? Options: specific files/directories, recent changes (git diff), or the entire project."
d. For entire-project scope, identify all source files (exclude vendored/generated code, build artifacts, lock files, and test fixtures). Prioritize by architectural significance: import fan-in/fan-out, file size, and recent change frequency. Distribute files across agents by relevance to each agent's domain.
e. Confirm scope with the user before proceeding: "I'll code-review [scope description]. Correct?"
Language & Project Detection
After determining scope, detect the primary language(s) and framework(s):
- Check file extensions, lock files (
package-lock.json,Pipfile.lock,Cargo.lock), and config/module files (tsconfig.json,pyproject.toml,Cargo.toml,go.mod,go.sum) - Set
primary_languageand note the framework(s) in use - Inform user: "Detected [language] project using [framework] — tailoring review accordingly."
- Check for project-level or user-level rule files (
rules/<language>.md, e.g.,rules/python.md) and instruct agents to read them if present for project-specific conventions.
Language detection shapes agent behavior — agents should apply language-idiomatic checks:
- Python: mutable default arguments, bare
except:, missing type hints on public APIs,os.pathvspathlib - JavaScript/TypeScript:
==vs===,varusage, unhandled promise rejections, missingasync/awaiterror handling, prototype pollution patterns - Go: unchecked errors, goroutine leaks, missing
deferfor cleanup, context propagation - Rust: unnecessary
.clone(), missing error propagation with?, overly broad lifetimes - Java: checked exception abuse, mutable DTOs, missing
@Override, raw types - Other languages: apply general software engineering principles
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.
- 3d ago Changed · +18 tokens per session 0e602404363c
- 1mo ago First seen · 189 lines · 23 tokens per session scan A c673e0fcbfbf
code-review is a skill published in the GitHub repository kimon1230/claude_extensions (4 stars, last pushed 2d ago), licensed MIT. It adds 41 tokens to every session and 3,945 once invoked, about $0.0002 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.
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