agentic-coding-playbook: Skill for Claude Code

.agents/skills/federal-agents-config/SKILL.md

federal-agents-config is a skill for Claude Code, Codex from GSA-TTS/agentic-coding-playbook. It costs 20 tokens per session (2,239 once invoked), scanned A, original, CC0-1.0.

An interactive guide that creates a project-specific AGENTS.md file, which is a set of instructions for an AI coding agent. It asks compliance questions and generates rules for the project while referring to shared federal guidance.

In plain words
What is it for?
Creating or updating agent instructions for federal projects, including projects involving FIPS, ATO, or federal compliance requirements.
Why use it?
It turns broad federal requirements into instructions suited to one project. It also prevents the project file from silently replacing the universal rules it depends on.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: installed under .agents/ (shared by several agents); mentions AGENTS.md; mentions Codex.

This is GSA-TTS/agentic-coding-playbook's own configuration. It tells Claude Code and Codex how to work on agentic-coding-playbook itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything agentic-coding-playbook configures →

Reuse

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.

Copy the file
curl -O https://raw.githubusercontent.com/GSA-TTS/agentic-coding-playbook/main/.agents/skills/federal-agents-config/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/GSA-TTS/agentic-coding-playbook

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for federal-agents-config

README.md
[![agentmods](https://agentmods.dev/badge/skills/gsa-tts/agentic-coding-playbook/federal-agents-config/github.svg)](https://agentmods.dev/skills/gsa-tts/agentic-coding-playbook/federal-agents-config)
Your own site
<a href="https://agentmods.dev/skills/gsa-tts/agentic-coding-playbook/federal-agents-config"><img src="https://agentmods.dev/badge/skills/gsa-tts/agentic-coding-playbook/federal-agents-config/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.

agentmods 80×15 button for federal-agents-config

Your own site · 80×15
<a href="https://agentmods.dev/skills/gsa-tts/agentic-coding-playbook/federal-agents-config"><img src="https://agentmods.dev/badge/skills/gsa-tts/agentic-coding-playbook/federal-agents-config.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 20 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,239 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 2 findings, 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 YARA Match · line 20
    YARA rule matched a hack tool or exploit indicator (offensive tools, reconnaissance, privilege escalation, or exploit frameworks).
    Fix: Remove offensive tool references and exploit code. Legitimate agent skills should not contain penetration testing tools, exploit frameworks, or reconnaissance utilities.
  • medium Excessive Agency · line 174
    Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.
    Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00020 $0.02239
Opus 5 $0.00010 $0.01120
Sonnet 5 $0.00004 $0.00448
Haiku 4.5 $0.00002 $0.00224

Measured 10d ago against content hash 651a006e4085, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

federal-agents-config 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 10d ago.

The scan reads SKILL.md. This mod also ships 2 executable files (scripts/generate-agents-md.py, scripts/validate-agents-md.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

.agents/skills/federal-agents-config/SKILL.md · 240 lines

How it starts

The opening of the file, as written. The whole thing — 240 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Federal AGENTS.md Configuration

This skill generates a project-specific AGENTS.md by walking the user through compliance-relevant questions and producing a customized behavioral contract.

The generated file is a thin, project-specific layer: it references the universal Federal AI Agent Behavioral Best Practices (the universal AGENTS.md) as a prerequisite and does NOT restate the universal rules. This keeps a single source of truth for the universal contract and avoids copy-paste drift. The generated file instructs the agent to STOP if it cannot confirm the universal contract is available, and to require the user's affirmative permission before proceeding without it.

When to Use

  • User needs to create an AGENTS.md for a new federal project
  • User wants to update their existing AGENTS.md for compliance
  • User asks "how do I configure my AI agent for federal requirements"
  • User mentions FIPS, ATO, or federal compliance in the context of agent setup

How It Works

  1. Ask the user compliance-relevant questions (elicitation sequence below)
  2. Accumulate answers into a JSON configuration object
  3. Run scripts/generate-agents-md.py with the config to produce AGENTS.md
  4. Present the output for human review
  5. Iterate if the user wants changes

Configuration Object

Track this JSON structure as you collect answers. Fields marked required must be filled before generation. Fields marked optional have sensible defaults.

{
  "system_name": null,
  "agency_name": null,
  "system_description": null,
  "impact_level": "moderate",
  "language": null,
  "framework": null,
  "data_classification": "internal",
  "ato_status": "pre-ato",
  "agent_names": [],
  "prohibited_actions": [],
  "permitted_actions": [],
  "approval_required_actions": [],
  "sensitive_data_types": [],
  "approved_storage": [],
  "secrets_backend": null,
  "approved_registries": [],
  "license_restrictions": [],
  "network_allowlist": [],
  "test_command": null,
  "test_coverage_target": "80",
  "ci_checks": ["lint", "test", "sast", "sca", "secrets-scan"],
  "branch_protection": "1 review, no force push",
  "project_lead": null,
  "security_contact": null,
  "isso_contact": null,
  "reviewed_by": null
}

Read the full file on GitHub · 240 lines

Files

What ships with it

4 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.

Changes

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.

  1. 10d ago First seen · 240 lines · 20 tokens per session scan A 651a006e4085

Subscribe to this mod's changes

federal-agents-config is a skill published in the GitHub repository GSA-TTS/agentic-coding-playbook (23 stars, last pushed 2d ago), licensed CC0-1.0. It adds 20 tokens to every session and 2,239 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 2026-08-30.

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