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-repo-setup/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-repo-setup)<a href="https://agentmods.dev/skills/gsa-tts/agentic-coding-playbook/federal-repo-setup"><img src="https://agentmods.dev/badge/skills/gsa-tts/agentic-coding-playbook/federal-repo-setup/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-repo-setup"><img src="https://agentmods.dev/badge/skills/gsa-tts/agentic-coding-playbook/federal-repo-setup.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 Privilege Escalation · line 61 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
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 | $0.00036 | $0.03365 |
| Opus 5 | $0.00018 | $0.01682 |
| Sonnet 5 | $0.00007 | $0.00673 |
| Haiku 4.5 | $0.00004 | $0.00336 |
Grade A, and why
federal-repo-setup 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.
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 — 447 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Federal Repository Setup
This skill converts the playbook in docs/GETTING-STARTED.md into an executable
workflow for initializing a repository with federal security compliance defaults.
When to Use
- Setting up a new code repository for federal AI development
- Hardening an existing repo to meet FIPS Moderate compliance baseline
- Adding missing security tooling (secrets scanning, SAST, dependency audit)
- Preparing a project for ATO review
Prerequisites
Before starting, confirm the user has:
- Git 2.39+ installed
- A supported language runtime (Python 3.10+, Node.js 18+, Go 1.21+, Java 17+, or .NET 8+)
- An approved AI coding agent (per agency policy)
- Access to pre-commit framework (
pip install pre-commitor equivalent)
Setup Procedure
Step 1: Detect Language and Framework
Examine the repository to determine the primary language and framework:
- Check for language indicators:
requirements.txt,pyproject.toml,setup.py-> Pythonpackage.json-> JavaScript/TypeScriptgo.mod-> Gopom.xml,build.gradle-> Java*.csproj,*.sln-> .NETCargo.toml-> Rust
- Check for framework indicators (package manifests, config files)
- If multiple languages, ask which is primary
Record the detected language — it determines which tools to recommend in later steps. See references/TOOL_MATRIX.md for the full language-to-tool mapping.
Step 2: Generate .gitignore
Create or update .gitignore with federal-required exclusion patterns.
Required patterns (all languages):
# === Federal Security: Secrets and Credentials ===
.env
.env.*
!.env.example
*.key
*.pem
*.p12
*.pfx
*.jks
credentials.*
**/secrets/
*.secret
# === Federal Security: IDE and Editor ===
.idea/
.vscode/settings.json
*.swp
*.swo
*~
# === Federal Security: OS Artifacts ===
.DS_Store
Thumbs.db
desktop.ini
Add language-specific patterns from https://github.com/github/gitignore for the detected language.
What ships with it
1 file 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.
- 10d ago First seen · 447 lines · 36 tokens per session scan A 902b563a7ef6
federal-repo-setup is a skill published in the GitHub repository GSA-TTS/agentic-coding-playbook (25 stars, last pushed today), licensed CC0-1.0. It adds 36 tokens to every session and 3,365 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.
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