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 agentmods add commands/ranyitz/aicm/reviewgit clone --depth 1 https://github.com/ranyitz/aicmWrote 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/ranyitz/aicm/review)<a href="https://agentmods.dev/commands/ranyitz/aicm/review"><img src="https://agentmods.dev/badge/commands/ranyitz/aicm/review.svg" alt="Measured on agentmods" 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 | $0.00000 | $0.00452 |
| Opus 5 | $0.00000 | $0.00226 |
| Sonnet 5 | $0.00000 | $0.00090 |
| Haiku 4.5 | $0.00000 | $0.00045 |
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 4d 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.
Code Review Before Commit
Review all current changes (typically all files are staged). Detect logical, structural, or quality issues, categorize them by severity, and ensure the code is ready to be committed.
1. Scope and Context
- Review the full diff between the current working directory and the last commit.
- If any files are modified but not staged, include them in the review and warn about them.
- Understand the intent of the change.
2. Critical Issues (must fix before commit)
Flag anything that could cause runtime or logical errors:
- Incorrect conditions, bad assumptions or unhandled cases.
- Public API changes or contract violations not reflected in docs.
- Inefficiencies or unnecessary complexity.
- Ensure no leftover debug logs.
3. Non-blocking Issues (nitpicks & improvements)
Provide suggestions for clarity, maintainability, and polish:
- Style / consistency - naming, formatting, comment clarity.
- Code structure - overly long functions, duplication, unclear separation of concerns.
- Docs / Comments - missing or outdated documentation, unclear logic.
- Tests - encourage new or updated tests for new logic.
4. Categorize & Summarize
Output structured feedback like this:
Critical:
- [ ] (file:line) Description
- [ ] (file:line) Description
Suggestions:
- [ ] (file:line) Description
Each item should be specific, actionable, and concise.
6. Commit Message Suggestion
- Summarize the intent of the changes and affected areas.
- Generate a concise, conventional commit message following this pattern:
<type>(<scope>): <short summary>
<optional longer description>
Examples of <type>: feat, fix, refactor, docs, test, chore.
Example:
feat(api): add support for async requests in data service
7. Commit Suggestion
After outputting the suggested commit message:
- Ask the user to confirm or edit it.
- Once confirmed, suggest running the equivalent of:
git commit -m "<final commit message>" - If the working tree is clean, suggest proceeding with the commit.
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.
- 4d ago First seen · 73 lines · 0 tokens per session scan A e2988058616a
review is a command published in the GitHub repository ranyitz/aicm (36 stars, last pushed 5mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 452 tokens. 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
git
Git operations with intelligent commit messages and workflow optimization.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.