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/rikdc/ai-skillsWrote 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/rikdc/ai-skills/review)<a href="https://agentmods.dev/commands/rikdc/ai-skills/review"><img src="https://agentmods.dev/badge/commands/rikdc/ai-skills/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 5.1 | $0.00012 | $0.00719 |
| Opus 5 | $0.00006 | $0.00360 |
| Sonnet 5 | $0.00002 | $0.00144 |
| Haiku 4.5 | $0.00001 | $0.00072 |
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.
How it starts
The opening of the file, as written. The whole thing — 103 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Advanced Code Review Command
You are an experienced Software Engineer conducting a comprehensive code review. Your task is to analyze code changes and provide actionable feedback using parallel analysis capabilities.
Usage
- Default: Reviews only changed files (modified/staged/recent commits)
--all: Reviews entire codebase for comprehensive analysis
Scope Determination
Check user arguments for --all flag
- If
--allpresent: Analyze entire repository codebase - Default behavior: Focus only on changed files from:
- Currently modified/staged files (
git status) - Files changed in recent commits (
git diff HEAD~1..HEADor similar) - Files in current working branch vs main/master
- Currently modified/staged files (
Execution Strategy
Spawn Sub-tasks for parallel processing:
- Task A: Git analysis and context gathering
- Task B: Code quality and security analysis
- Task C: Edge case and robustness evaluation
Sub-task Instructions
Task A: Repository Context Analysis
- Verify git repository and retrieve latest commit details
- Identify current branch and relationship to main/master
- Determine review scope based on arguments:
- Default: Identify changed files only (
git status,git diff, branch comparison) - With
--all: Prepare for full repository analysis
- Default: Identify changed files only (
- Analyze scope of changes (files modified, lines changed, change types)
- Flag any merge conflicts or unusual git states
Task B: Code Quality Review
- Review target files based on scope determination from Task A
- Analyze code for:
- Performance: Identify bottlenecks, inefficient algorithms, resource usage
- Security: Check for vulnerabilities, input validation, authentication issues
- Maintainability: Assess readability, documentation, code organization
- Standards Compliance: Verify adherence to team/language conventions
- Ignore placeholder TODOs and incomplete implementations
- Focus efficiency: With default scope, concentrate on changed areas and their immediate context
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.
- 8d ago First seen · 103 lines · 12 tokens per session scan A 91d40b5c3308
review is a command published in the GitHub repository rikdc/ai-skills (2 stars, last pushed 2d ago), licensed MPL-2.0. It adds 12 tokens to every session and 719 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 2026-08-31.
Other commands, from other repositories
discover
Run a full product discovery cycle — from outcome definition through opportunity mapping, prioritisation, and experiment design. Use when the team isn't sure what to build next, or before writing a PRD for a complex feature space.
tax-review
Tax-filing compliance check — invokes tax-reviewer to produce TM-tax-{slug}.md with MeF e-file schema, Form 8879, PTIN/Circular 230, and IRC §7216 consent gaps.
voice-compliance
Voice/telephony compliance check — invokes voice-ai-reviewer to produce TM-voice-{slug}.md with TCPA, STIR/SHAKEN, state recording-consent, EU AI Act Art. 50, and synth-voice deepfake-law gaps.
simplify
The over-engineering review: five tags (delete, stdlib, native, yagni, shrink), a mandatory replacement per finding, and a real null result when there is nothing to cut.
git
The pre-finish status: branch, hygiene findings, message checks, workflow lint, template state.
init
Install the formatters this repository needs, with every command visible before it runs.