Borrowing it
Nothing to install: this file belongs to GSA-TTS/agentic-coding-playbook. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/GSA-TTS/agentic-coding-playbook/main/.agents/skills/federal-security-controls-lookup/SKILL.mdgit clone --depth 1 https://github.com/GSA-TTS/agentic-coding-playbookWrote 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/gsa-tts/agentic-coding-playbook/federal-security-controls-lookup)<a href="https://agentmods.dev/skills/gsa-tts/agentic-coding-playbook/federal-security-controls-lookup"><img src="https://agentmods.dev/badge/skills/gsa-tts/agentic-coding-playbook/federal-security-controls-lookup/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/gsa-tts/agentic-coding-playbook/federal-security-controls-lookup"><img src="https://agentmods.dev/badge/skills/gsa-tts/agentic-coding-playbook/federal-security-controls-lookup.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00034 | $0.01418 |
| Opus 5 | $0.00017 | $0.00709 |
| Sonnet 5 | $0.00007 | $0.00284 |
| Haiku 4.5 | $0.00003 | $0.00142 |
Grade A, and why
federal-security-controls-lookup 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 12d 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 — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Federal Security Controls Lookup
This skill navigates the federal agentic AI guidance repository to find relevant policy documents, checklist items, and remediation guidance for a given security control, OWASP risk, or keyword.
When to Use
- User asks about a specific NIST control (e.g., "What does AC-6 require?")
- User asks about an OWASP risk (e.g., "How do we handle LLM01 prompt injection?")
- User asks a security question (e.g., "How should we handle secrets?")
- User needs to trace a checklist failure back to guidance
- User needs to understand which controls apply to a topic
Lookup Procedure
Step 1: Classify the Query
Determine which type of lookup the user needs:
| Query Pattern | Type | Example |
|---|---|---|
AC-*, AU-*, CM-*, IA-*, IR-*, RA-*, SA-*, SC-*, SI-*, SR-* |
NIST Control ID | "AC-6", "SI-10" |
LLM01-LLM10 |
OWASP LLM Risk | "LLM01" |
Agentic-01-Agentic-10 |
OWASP Agentic Risk | "Agentic-05" |
Checklist number like 1.1, 5.3 |
Checklist Item | "item 2.5" |
| Free text | Keyword Search | "secrets", "input validation" |
Step 2: Read the Traceability Matrix
Read docs/TRACEABILITY.md — this is the navigation index for the entire repository.
It contains five mapping tables:
- NIST Control -> Document sections (Table 1)
- OWASP LLM Risk -> Controls and sections (Table 2a)
- OWASP Agentic Risk -> Controls and sections (Table 2b)
- Checklist Item -> Control and guidance (Table 3, items 1.1-10.6)
- AI RMF Function -> Documents (Table 4)
Step 3: Follow the Lookup Path
For NIST Control IDs (e.g., AC-6)
- Find the control in Table 1 of
docs/TRACEABILITY.md - Note which document sections are referenced (e.g.,
AGENTS.md §3.1,SECURITY-CONTROLS.md §3.1) - Note which checklist items verify this control
- Read the referenced sections from those documents
- Present: control name, where guidance lives, what the checklist verifies, key requirements
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.
- 12d ago First seen · 135 lines · 34 tokens per session scan A a3744abe5b30
federal-security-controls-lookup is a skill published in the GitHub repository GSA-TTS/agentic-coding-playbook (25 stars, last pushed 2d ago), licensed CC0-1.0. It adds 34 tokens to every session and 1,418 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…