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.
git clone --depth 1 https://github.com/penwyp/ClaudePreferenceWrote 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/penwyp/claudepreference/m-review-code)<a href="https://agentmods.dev/commands/penwyp/claudepreference/m-review-code"><img src="https://agentmods.dev/badge/commands/penwyp/claudepreference/m-review-code/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/penwyp/claudepreference/m-review-code"><img src="https://agentmods.dev/badge/commands/penwyp/claudepreference/m-review-code.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 | $0.00000 | $0.00760 |
| Opus 5.5 | $0.00000 | $0.00304 |
| Sonnet 5.5 | $0.00000 | $0.00152 |
| Haiku 4.5 | $0.00000 | $0.00076 |
Grade A, and why
m-review-code 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 1mo 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 — 112 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Review Workflow: Comprehensive Analysis & Report Generation
Target: $ARGUMENTS (Default: latest commits of current branch)
Scope: Analyze code changes, architecture patterns, and implementation quality
Execution Steps
-
Architecture & Pattern Analysis
- Review repository patterns, service layers, and migration strategies
- Assess system design decisions and structural changes
-
Security & Multi-tenant Validation
- Check authentication, authorization, and tenant isolation
- Identify potential security vulnerabilities and access control issues
-
Functional Completeness Verification
- Ensure all requirements are implemented with proper edge case handling
- Validate input validation, error handling, and boundary conditions
-
Code Quality Assessment
- Identify code smells, anti-patterns, and duplicated logic
- Detect potential runtime issues: race conditions, memory leaks, null pointer exceptions
-
Test Coverage Evaluation
- Assess unit and integration test coverage gaps
- Review test quality and edge case coverage
-
Third-party Library Opportunities
- Suggest robust external libraries for current implementations
- Identify opportunities to reduce custom code complexity
-
Generate Bilingual Report
- Compile findings into structured markdown format
- Save to
docs/workspaces/review-MM-dd-HH-mm-ss.md
Output Format
English Report
Present findings in the following sections:
functionalCompleteness
- Requirements implementation status
- Edge case handling assessment
- Missing functionality identification
criticalBugs
- Potential crashes, panics, or system failures
- Security vulnerabilities and data exposure risks
- Performance bottlenecks and resource leaks
badSmells
- Code anti-patterns and design issues
- Duplicated or overly complex logic
- Maintainability concerns
thirdPartyOpportunities
- External library suggestions for current implementations
- Benefits and integration considerations
- Risk assessment for library adoption
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.
- 1mo ago First seen · 112 lines · 0 tokens per session scan A 7685d825ad14
m-review-code is a command published in the GitHub repository penwyp/ClaudePreference (136 stars, last pushed 4mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 760 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
refactor
Systematic code refactoring with smart scope detection.
review-branch
Review the current branch's diff against base by dispatching atomic-reviewer. No orchestration loop, no spec required — pre-flight before /commit pr or /commit merge.
init
Install the formatters this repository needs, with every command visible before it runs.
merge-conflict-analysis
You are analyzing merge conflicts for PR #${{ pr-number }}.
boot
Start a new PromptKit prompt assembly session (alias for /bootstrap).
repo-audit
Audit a codebase (local or remote GitHub/GitLab) against architecture principles and requirements, surfacing drift, risk, and missing decisions.