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 skills/neurofoo/agent-skills/aarnpx skills add neurofoo/agent-skills --skill aargit clone --depth 1 https://github.com/neurofoo/agent-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/skills/neurofoo/agent-skills/aar)<a href="https://agentmods.dev/skills/neurofoo/agent-skills/aar"><img src="https://agentmods.dev/badge/skills/neurofoo/agent-skills/aar.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 | $0.00039 | $0.00607 |
| Opus 5 | $0.00019 | $0.00303 |
| Sonnet 5 | $0.00008 | $0.00121 |
| Haiku 4.5 | $0.00004 | $0.00061 |
Grade A, and why
aar 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 5d 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.
After-Action Review
Conduct a structured debrief to extract learning from any significant event or experience.
Instructions
Work through the four core questions honestly and specifically. Focus on events and systems, not blaming individuals.
Output Format
Event: What are we reviewing? Date: When did it happen? Participants: Who was involved?
1. What Was Expected?
Before the event, what did we think would happen?
Goals/Objectives
- [What were we trying to achieve?]
Plan
- [What was the plan to achieve it?]
Success Criteria
- [How would we know if we succeeded?]
Assumptions
- [What did we assume would be true?]
2. What Actually Happened?
Facts only—what occurred, not why
Timeline
| Time | Event |
|---|---|
| [When] | [What happened] |
Outcomes
- [What results did we get?]
Compared to Expected
| Expected | Actual | Gap |
|---|---|---|
| [expectation] | [reality] | [+/-] |
3. Why the Difference?
Analysis of the gap between expected and actual
What Went Well (sustain these)
| Success | Contributing Factors |
|---|---|
| [what worked] | [why it worked] |
What Didn't Go Well (improve these)
| Problem | Root Cause |
|---|---|
| [what failed] | [why it failed] |
Surprises
- [Things we didn't anticipate]
4. What Do We Do Next?
Specific actions to sustain or improve
Sustain (keep doing these)
| Action | Owner | How to Protect It |
|---|---|---|
| [what to continue] | [who] | [mechanism] |
Improve (change these)
| Action | Owner | By When |
|---|---|---|
| [what to change] | [who] | [deadline] |
Key Takeaways Top 3 lessons from this review:
- [Lesson]
- [Lesson]
- [Lesson]
Follow-up When will we check if improvements are working?
Guidelines
- Do this soon—memory fades fast
- Be specific: "Communication failed" → "We didn't update Slack until hour 3"
- Balance: Include what went well, not just problems
- Assign owners: Insights without ownership become forgotten
- Make it safe: Blame shuts down honesty
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 5d ago First seen · 113 lines · 39 tokens per session scan A 0704fde2bc21
aar is a skill published in the GitHub repository neurofoo/agent-skills (111 stars, last pushed 7mo ago), licensed MIT. It adds 39 tokens to every session and 607 once invoked, about $0.0002 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 skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…