Borrowing it
Nothing to install: this file belongs to jens-duttke/usage-monitor-for-claude. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/jens-duttke/usage-monitor-for-claude/main/.claude/commands/review.mdgit clone --depth 1 https://github.com/jens-duttke/usage-monitor-for-claudeWrote 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/commands/jens-duttke/usage-monitor-for-claude/review)<a href="https://agentmods.dev/commands/jens-duttke/usage-monitor-for-claude/review"><img src="https://agentmods.dev/badge/commands/jens-duttke/usage-monitor-for-claude/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/commands/jens-duttke/usage-monitor-for-claude/review"><img src="https://agentmods.dev/badge/commands/jens-duttke/usage-monitor-for-claude/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 | $0.00013 | $0.01102 |
| Opus 5 | $0.00006 | $0.00551 |
| Sonnet 5 | $0.00003 | $0.00220 |
| Haiku 4.5 | $0.00001 | $0.00110 |
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 12d 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 — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Perform a systematic quality review of all staged changes. Work through the following steps sequentially. Use the full context of this conversation to understand WHY the changes were made.
Step 1: Critical Code Review
Run git diff --staged and critically review EVERY changed file:
Correctness & Logic
- Are all changes meaningful and actually necessary for the intended implementation?
- Off-by-one errors, boundary conditions, edge cases (empty inputs, None values, zero-length collections)?
- State management - can objects be left in invalid states?
- Order dependencies - do operations assume a specific sequence without enforcing it?
Code Quality
- Can existing code be simplified or removed as a result of these changes (dead code, duplicates)?
- Is there optimization potential (performance, readability, maintainability)?
- Are naming conventions and code style consistent with CLAUDE.md rules?
- When a comment is corrected because the described behavior changed, check immediately whether the same outdated concept is also encoded in nearby variable, parameter, or function names - and rename them too.
- No ambiguous names like
other,data2,flag- every name must be immediately clear.
Security (especially for changes touching api.py)
- No credentials in logs, error messages, or anywhere outside HTTP Authorization headers.
- All URLs and API endpoints are top-level constants - no dynamic URL construction.
- No
eval(),exec(),compile(), or dynamic imports. - No file write operations (the app is read-only).
- No obfuscation, no base64-encoded strings, no encoded URLs or tokens.
- Network communication exclusively with
api.anthropic.com.
Concurrency & Resource Management
- Race conditions in threading code (check-then-act patterns, shared mutable state)?
- Proper cleanup of resources in error paths (context managers, finally blocks)?
- Timeout handling on blocking operations?
Error Handling & Resilience
- Proper input validation at function boundaries?
- Early returns and guard clauses used consistently?
- Error messages provide enough context for debugging without leaking sensitive data?
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.
- 12d ago First seen · 113 lines · 13 tokens per session scan A 992092f7c118
review is a command published in the GitHub repository jens-duttke/usage-monitor-for-claude (282 stars, last pushed 2d ago), licensed MIT. It adds 13 tokens to every session and 1,102 once invoked, about $0.0001 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.
Other commands, from other repositories
notebook-review
Comprehensive review of Jupyter notebooks and Python scripts.
cpp-review
Comprehensive C++ code review for memory safety, modern C++ idioms, concurrency, and security. Invokes the cpp-reviewer agent.
refactor-clean
Remove dead code and consolidate duplicates.
rust-review
Rust code review for ownership, safety, and idiomatic patterns.
refactor
Clean up dead code, reduce duplication, and simplify structure without changing behavior.
quality-gate
Run the ECC quality pipeline on demand for a file or project scope.