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-decision-records/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-decision-records)<a href="https://agentmods.dev/skills/gsa-tts/agentic-coding-playbook/federal-decision-records"><img src="https://agentmods.dev/badge/skills/gsa-tts/agentic-coding-playbook/federal-decision-records/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-decision-records"><img src="https://agentmods.dev/badge/skills/gsa-tts/agentic-coding-playbook/federal-decision-records.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 | $0.00027 | $0.02017 |
| Opus 5.5 | $0.00011 | $0.00807 |
| Sonnet 5.5 | $0.00005 | $0.00403 |
| Haiku 4.5 | $0.00003 | $0.00202 |
Grade A, and why
federal-decision-records 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 1mo 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 — 221 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Federal Decision Records
This skill helps users create, validate, and index architectural and security decision records using MADR (Markdown Any Decision Records) format with federal compliance extensions.
Decision records provide an audit trail linking design choices to NIST controls and risk treatment rationale — required for ATO documentation.
| Path | Kind | Notes |
|---|---|---|
docs/CODING_PRACTICES.md |
playbook-source | Cited as a policy reference for coding decisions. See AGENTS.md §13.1a if not found at this relative path. |
docs/SECURITY-CONTROLS.md |
playbook-source | Cited as a policy reference for control guidance. See AGENTS.md §13.1a if not found at this relative path. |
| docs/TRACEABILITY.md | playbook-source | The playbook's control-mapping matrix (in the agentic-coding-playbook repo). See AGENTS.md §13.1a if not found at this relative path. |
docs/decisions/ |
target-project | Default output directory for generated ADRs in the target repo (Step 5 asks the user to confirm); never resolved via §13.1a. |
references/DECISION_CATEGORIES.md, references/ADR_TEMPLATE.md |
bundled (skill-local) | Self-contained regardless of symlink location; not looked up via §13.1a. |
When to Use
- Documenting a decision about AI agent authorization or capabilities
- Recording data handling or classification decisions
- Capturing deployment or infrastructure security choices
- Documenting cryptographic or authentication design decisions
- Preparing audit trail for ISSO or ATO reviewer
- When the
federal-risk-assessmentskill identifies risks that require treatment decisions — document the treatment rationale here
How It Works
This skill has three modes:
- Create — Guide the user through creating a new decision record
- Validate — Check existing ADRs for format and completeness
- Index — Generate a decision record index from frontmatter
Ask the user which mode they need, or infer from context.
What ships with it
2 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.
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.
- 1mo ago Changed · +9 lines 90b946234924
- 1mo ago First seen · 212 lines · 27 tokens per session scan A 9e7872ed09b2
federal-decision-records is a skill published in the GitHub repository GSA-TTS/agentic-coding-playbook (37 stars, last pushed yesterday), licensed CC0-1.0. It adds 27 tokens to every session and 2,017 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.
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