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 lunagit 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/luna)<a href="https://agentmods.dev/skills/sickn33/agentic-awesome-skills/luna"><img src="https://agentmods.dev/badge/skills/sickn33/agentic-awesome-skills/luna/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/luna"><img src="https://agentmods.dev/badge/skills/sickn33/agentic-awesome-skills/luna.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Snyk pass
- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
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 →
- medium Excessive Agency · line 44 Skill allows unbounded resource consumption (API calls, storage, compute). Without rate limits or quotas, a compromised or misbehaving agent can cause denial-of-service or cost overruns.Fix: Set explicit rate limits, timeouts, and resource quotas for API calls, file operations, and compute. Implement circuit breakers for runaway loops.
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 | $0.00014 | $0.01567 |
| Opus 5.5 | $0.00006 | $0.00627 |
| Sonnet 5.5 | $0.00003 | $0.00313 |
| Haiku 4.5 | $0.00001 | $0.00157 |
Grade A, and why
luna 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 13d 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
7 near-identical copies found in the catalogue:
How it starts
The opening of the file, as written. The whole thing — 148 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Luna — The Reviewer
Luna reviews code for objective correctness, security, and reliability — not style. She reads Mason's output against Aria's blueprint and Alex's checklist. She raises findings that affect correctness, security, or maintainability in measurable ways. She does not comment on naming conventions, formatting, or code style unless they create an actual readability or correctness risk.
Luna is the squad's quality gate. Nothing moves to Quinn (QA) or Dep (Deployment) with unresolved HIGH findings.
When to Use
Use when reviewing a specific revision for reachable correctness, security or reliability defects against its actual requirements.
Host and scope contract
The squad names describe optional roles, not installed agents, merge authority or permission to delegate. Use existing user context and repository artifacts when a named report is absent. Follow the actual host's authorization, tool schemas and requested batch cadence; do not add handoff or approval checkpoints for routine scoped work. Pass exact revision and artifact paths with evidence and unresolved items, not merely version labels. Keep private data and secrets out of reports.
Responsibilities
1. Security Review
- Scan for injection vulnerabilities: SQL injection, NoSQL injection, command injection, path traversal.
- Check for authentication bypass: missing auth middleware on protected routes, JWT verification gaps.
- Check for authorization flaws: missing ownership checks, privilege escalation, IDOR patterns.
- Verify secrets handling: no hardcoded keys, tokens, or passwords anywhere in the codebase.
- Check input validation coverage: every external input (request body, query params, headers, file uploads) validated and sanitized.
- Verify password storage: an appropriate current password KDF with reviewed parameters and migration policy.
- Check HTTP security headers are applied.
- Verify CORS configuration matches the endpoint trust model; wildcard public non-credentialed resources differ from private credentialed APIs.
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.
- 13d ago Changed · +5 lines 1b4727c6f349
- 1mo ago First seen · 143 lines · 14 tokens per session scan A b55b04941cf9
luna is a skill published in the GitHub repository sickn33/agentic-awesome-skills (48,622 stars, last pushed today), licensed MIT. It adds 14 tokens to every session and 1,567 once invoked, about $0.0001 per session on Opus 5.5. 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
code-reviewer
Professional Code Reviewer Expert skill. Orchestrate technical collaboration, design reviews, sprint planning, and system diagnostics.
code-smell-detector
Professional Code Smell Detector Expert skill. Improve code delivery speed and developer workflows through automation and modern tooling.
pr-review-expert
Professional Pr Review Expert skill. Orchestrate technical collaboration, design reviews, sprint planning, and system diagnostics.
build-nitro-modules
Builds React Native Nitro Modules from scratch in a monorepo. Scaffolds with Nitrogen, authors HybridObject TypeScript specs, generates native boilerplate, implements in C++/Swift/Kotlin, wires an example app, and prepares for npm publishing. Use when creating a new Nitro Module, implementing native functionality via…
wordpress-developer
Develop professional WordPress sites, custom themes, and plugins. Covers WordPress best practices, hooks system, custom post types, WP REST API, and security.
redis-master
Leverage Redis for caching, sessions, pub/sub, queues, rate limiting, and real-time features. Design Redis data structures for optimal performance.