federal-decision-records
Create, validate, and index architectural and security decision records using MADR format with federal compliance extensions.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
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Create, validate, and index architectural and security decision records using MADR format with federal compliance extensions.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
Detect available credentials, diagnose gaps against PROJECT_PLAN.md, and guide setup for AI agents in any environment
Collect and verify all ATO submission artifacts into a review-ready package
Deploy applications to cloud.gov — sandbox setup, manifest generation, CI/CD pipeline
Review AI-assisted code changes and create compliant pull requests with proper attribution
Run the 62-item federal pre-deployment security checklist against a codebase.
Initialize a code repository with federal security compliance defaults including .gitignore, pre-commit hooks, .editorconfig, and CI/CD security baseline.
| name | federal-decision-records |
| title | Federal Decision Records |
| description | Create, validate, and index architectural and security decision records using MADR format with federal compliance extensions. |
| status | canonical |
| tier | 2 |
| last_updated | 2026-06-01 |
| load_priority | on-demand |
| audience | ["developers","agents"] |
| triggers | ["ADR","architecture decision","decision record"] |
| dependencies | [] |
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.
federal-risk-assessment skill identifies risks that require
treatment decisions — document the treatment rationale hereThis skill has three modes:
Ask the user which mode they need, or infer from context.
Ask the user what kind of decision they are documenting. Present the categories from references/DECISION_CATEGORIES.md:
"What category does this decision fall into?"
Read references/DECISION_CATEGORIES.md to present the current category list
with examples. Each category maps to relevant NIST controls.
Ask for the required fields:
"Let's document this decision. I need:
- Title — What is being decided? (Use format: 'Use X for Y')
- Status — proposed, accepted, deprecated, or superseded?
- Decision makers — Who is involved in this decision?
- Date — When was this decided? (Default: today)"
These extend standard MADR with federal context:
"For federal compliance traceability:
- NIST controls — Which 800-53 controls does this decision address? (I can suggest controls based on the category you selected)
- Impact level — Low, Moderate, or High (FIPS 199)?
- ATO relevance — Is this decision relevant to the ATO package? (yes-boundary, yes-internal, no)
- Risk treatment — If this addresses a known risk, what treatment? (mitigate, transfer, accept, avoid, or N/A)"
Use the category-to-control mapping from references/DECISION_CATEGORIES.md
to suggest relevant NIST controls. The user can accept, modify, or skip.
Walk through each MADR section. Read the template at references/ADR_TEMPLATE.md to get the current section structure. For each section:
Context and Problem Statement:
"Describe the problem or context that led to this decision. What question are you trying to answer? (1-3 sentences)"
Decision Drivers:
"What factors influenced this decision? List the key drivers."
Suggest compliance-relevant drivers based on the category:
Considered Options:
"What options did you evaluate? List 2-4 alternatives."
For each option, ask for a brief description.
Decision Outcome:
"Which option was chosen, and why?"
Consequences:
"What are the positive and negative consequences of this decision?"
Prompt specifically for compliance consequences:
"Are there any compliance implications? (e.g., additional controls needed, ATO documentation updates, monitoring requirements)"
Check the target directory for existing ADRs:
"Where should decision records be stored? (Default:
docs/decisions/)"
Scan the directory for existing NNNN-*.md files and assign the next
sequential number (zero-padded to 4 digits).
Produce the complete ADR file using the template from
references/ADR_TEMPLATE.md with all collected information filled in.
Present the generated record for review:
"Here is the generated decision record. Review it and let me know if you'd like any changes before I save it."
Save to {directory}/{NNNN}-{slugified-title}.md.
After saving, run the index generator:
make generate
This updates {directory}/README.md with a table of all decision records
derived from their frontmatter.
Based on the decision category, suggest follow-up actions:
federal-agents-config to update AGENTS.md
with the authorized agents and capabilities from this decision"federal-risk-assessment if data classification changed"federal-pre-deployment-check to verify the
deployment configuration matches this decision"Run the validation script:
PYTHONPATH=scripts python3 -m playbook_validator validate-adrs --dir docs/adr
The script checks:
NNNN-title.md conventionXX-N or XX-N(N))Output is structured JSON. Present results to the user with remediation guidance for any failures.
Run the index generator to rebuild the decision record index:
make generate
This reads frontmatter from all ADR files and generates a README.md in the
decisions directory with:
Present the generated index to the user.
AGENTS.md (agent decisions), docs/CODING_PRACTICES.md
(coding decisions), docs/SECURITY-CONTROLS.md (control guidance),
docs/TRACEABILITY.md (control mappings).