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 lwalden/AIAgentMinder --skill self-reviewgit clone --depth 1 https://github.com/lwalden/AIAgentMinderWrote 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/lwalden/aiagentminder/self-review)<a href="https://agentmods.dev/skills/lwalden/aiagentminder/self-review"><img src="https://agentmods.dev/badge/skills/lwalden/aiagentminder/self-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/lwalden/aiagentminder/self-review"><img src="https://agentmods.dev/badge/skills/lwalden/aiagentminder/self-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 | $0.00009 | $0.01333 |
| Opus 5 | $0.00005 | $0.00666 |
| Sonnet 5 | $0.00002 | $0.00267 |
| Haiku 4.5 | $0.00001 | $0.00133 |
Grade A, and why
self-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 — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/aiagentminder:self-review - Pre-PR Code Review
Run a focused code review before creating a pull request. Spawns dedicated reviewer agents — each with a specific lens, read-only permissions, and its own context window.
Step 1: Get the Diff
Get the diff for the current branch vs main (or the base branch):
git diff main...HEAD
If the diff is empty: tell the user "No changes vs main — nothing to review."
Step 2: Choose Review Lens
During autonomous sprint execution: lens selection is the caller's responsibility (sprint-master selects lenses based on PR content type before invoking this skill). Run only the lenses passed in the invocation prompt. If no specific lenses are specified, ask the user which to apply (same as manual invocation below).
When invoked manually, ask the user which lens to apply:
A) Security — injection, auth bypass, data exposure, hardcoded secrets B) Performance — N+1 queries, unbounded loops, missing indexes, blocking I/O C) API Design — consistency with existing endpoints, naming conventions, error response shapes D) Cost Impact — paid API call patterns, retry/fallback designs, unbounded batch sizes E) UX Friction — error messages, CLI output, feedback, discoverability F) All five (default)
Step 3: Run the Review
For each selected lens, use the Agent tool to spawn the corresponding reviewer agent. Pass the diff as the prompt — the agent's own instructions define its focus areas and output format.
| Lens | Agent | Notes |
|---|---|---|
| Security | security-reviewer |
disallowedTools: [Edit, Write, Bash], model: sonnet, effort: high |
| Performance | performance-reviewer |
disallowedTools: [Edit, Write, Bash], model: sonnet, effort: high |
| API Design | api-reviewer |
disallowedTools: [Edit, Write, Bash], model: sonnet, effort: medium |
| Cost Impact | cost-reviewer |
disallowedTools: [Edit, Write, Bash], model: sonnet, effort: medium |
| UX Friction | ux-reviewer |
disallowedTools: [Edit, Write, Bash], model: sonnet, effort: medium |
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 · 128 lines · 9 tokens per session scan A 64eb3d38d63b
self-review is a skill published in the GitHub repository lwalden/AIAgentMinder (5 stars, last pushed 1mo ago), licensed MIT. It adds 9 tokens to every session and 1,333 once invoked, about $0.0000 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 skills, from other repositories
cn-check
Install and run the Continue CLI (cn) to execute AI agent checks on local code changes. Use when asked to "run checks", "lint with AI", "review my changes with cn", or set up Continue CI locally.
github-commenting
How to post clean, rich, deduplicated GitHub PR review comments — suggestion blocks, multi-line anchors, markers, formatting rules. Load before posting or fixing any PR comment.
repo-conventions
NeuroLink's review standards — the critical rules to enforce, what NOT to comment on, the security bar, hot paths. Load before reviewing any change in this repository.
joycraft-design
Design discussion before decomposition — produce a 200-line design artifact for human review, catching wrong assumptions before they propagate into specs.
joycraft-spec-done
Lightweight per-spec wrap-up — bump status to in-review, terse discovery if surprised, commit. Run after each spec in checkpoint/isolated mode; no validation, no push, no PR.
PR Etiquette
This skill should be used when responding to maintainer review feedback, writing or reviewing PR descriptions, following up on dormant PRs, validating PR quality before submission, or deciding how to communicate with maintainers. Sibling to oss-contribution and contribution-ethics.