AAS Core is a local control plane for coding agents that lets them search a large catalogue of skills, choose a stack, validate it, and create a reproducible plan. It is used to assemble and review agent workflows through its CLI, local MCP server, catalogue, plugins, and Workbench. The catalogue add-ons provide the skills, plugins, bundles, and workflows that AAS Core helps agents select and validate.
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 sickn33/agentic-awesome-skills --skill ask-mattgit clone --depth 1 https://github.com/sickn33/agentic-awesome-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/sickn33/agentic-awesome-skills/ask-matt)<a href="https://agentmods.dev/skills/sickn33/agentic-awesome-skills/ask-matt"><img src="https://agentmods.dev/badge/skills/sickn33/agentic-awesome-skills/ask-matt/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/sickn33/agentic-awesome-skills/ask-matt"><img src="https://agentmods.dev/badge/skills/sickn33/agentic-awesome-skills/ask-matt.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Memory Poisoning · line 47 Skill manipulates agent memory, state, or stored context. Memory corruption can alter personality, override safety rules, or cause unpredictable behavior.Fix: Protect agent memory and state from modification by untrusted content. Use read-only memory for critical instructions and validate all state changes.
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 | $0.00026 | $0.01326 |
| Opus 5 | $0.00013 | $0.00663 |
| Sonnet 5 | $0.00005 | $0.00265 |
| Haiku 4.5 | $0.00003 | $0.00133 |
Grade A, and why
ask-matt 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 3d 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.
Copies of this mod
8 near-identical copies found in the catalogue:
- ask-matt — 100% identical, 5 lines differ
- ask-matt — 100% identical, 5 lines differ
- ask-matt — 100% identical, 5 lines differ
- ask-matt — 100% identical, 5 lines differ
- ask-matt — 89% identical, 36 lines differ
- ask-matt — 89% identical, 36 lines differ
- ask-matt — 89% identical, 40 lines differ
- ask-matt — 89% identical, 36 lines differ
How it starts
The opening of the file, as written. The whole thing — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ask Matt
When to Use
Use when this workflow matches the user request: Ask which skill or flow fits your situation. A router over the user-invoked skills in this repo.
Source: mattpocock/skills (MIT).
You don't remember every skill, so ask.
A flow is a path through the skills. Most paths run along one main flow, and two on-ramps merge onto it. Everything else is standalone.
The main flow: idea → ship
The route most work travels. You have an idea and want it built.
/grill-with-docs— sharpen the idea by interview. Start here when you have a codebase: it's stateful, retaining what it learns inCONTEXT.mdand ADRs. (No codebase? Use/grill-me— see Standalone.)- Branch — can you settle every question in conversation? If a question needs a runnable answer (state, business logic, a UI you have to see), detour through a prototype, bridged by
/handoffin both directions (see Crossing sessions):/handoffout, then open a fresh session against that file,/prototypeto answer the question with throwaway code,/handoffback what you learned, and reference it from the original idea thread.
- Branch — is this a multi-session build?
- Yes →
/to-prd(turn the thread into a PRD) →/to-issues(split the PRD into independently-grabbable issues). Because the issues are independent, clear context between each one: start a fresh session per issue and kick off/implementby passing it the PRD and the single issue to work on. - No →
/implementright here, in the same context window.
- Yes →
Context hygiene
Keep steps 1–3 in one unbroken context window — don't compact or clear until after /to-issues — so the grilling, PRD, and issues all build on the same thinking. Each /implement then starts fresh, working from the issue.
The limit on this is the smart zone: the window (~120k tokens on state-of-the-art models) within which the model still reasons sharply. If a session approaches it before /to-issues, don't push on degraded — /handoff and continue in a fresh thread.
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.
- 3d ago Changed · +5 lines d686175588bd
- 6d ago First seen · 93 lines · 26 tokens per session scan A bb7525453aad
ask-matt is a skill published in the GitHub repository sickn33/agentic-awesome-skills (46,230 stars, last pushed yesterday), licensed MIT. It adds 26 tokens to every session and 1,326 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 2026-09-05.
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