菜单
Extract clear, structured requirements from a user request. Use when decomposing intent into functional, non-functional, and constraint requirements.
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。
基于 SOC 职业分类
Generate and maintain AI_STANCE.md for any uFawkes* repo. Use when onboarding a repo to the uFawkesAI suite, when reviewing AI policy currency, or when a new AI tool is being adopted. Implements DORA AI Capability 1.
Ensure graphify corpus is current and complete before each agent session. Define minimum AI-accessible documentation per repo. Use at session startup to verify internal context is available to AI tools. Implements DORA AI Capability 3.
15-minute JTBD + acceptance criterion exercise. Use before any spec session. Produces a discovery-brief.md that anchors the entire increment to a real user need and a measurable DORA outcome. Implements DORA AI Capability 6.
Enforce minimum documentation standard across uFawkes* repos. Use when auditing a repo before release, onboarding a new repo to the suite, or implementing roadmap item 0.6 (cross-repo README links). Directly supports DORA AI Capability 3 and the 2023 DORA finding that documentation quality amplifies all technical capabilities.
Create and manage DOJO content for platform engineering education and knowledge sharing.
Maintain AI_STANCE.md as a living document. Use quarterly or when a new AI tool is adopted. Handles review triggers, the three-bucket update process, socialization checklist, and cross-repo consistency. Companion to ai-stance skill.
| name | requirements-extraction |
| description | Extract clear, structured requirements from a user request. Use when decomposing intent into functional, non-functional, and constraint requirements. |
| license | MIT |
| compatibility | Claude Code, GitHub Copilot, OpenCode, Cursor, Codex, Gemini CLI |
| metadata | {"author":"paruff","suite":"uFawkesAI"} |
Load trigger:
"load requirements-extraction skill"> DORA: Cap 3 (AI-Accessible Internal Data) Token cost: Low
Extract clear, structured requirements from a user request.
AGENTS.md, docs/)requirements.jsonconstraints.jsonnonfunctional.json{
"functional": [
{
"id": "REQ-001",
"title": "Requirement title",
"description": "What the system must do",
"priority": "must-have | should-have | nice-to-have"
}
],
"nonfunctional": [
{
"id": "NFR-001",
"category": "performance | security | scalability | availability",
"description": "Specific requirement"
}
],
"constraints": [
{
"id": "CON-001",
"type": "technical | business | regulatory",
"description": "Constraint description"
}
],
"assumptions": ["Assumption 1"],
"dependencies": ["External system X"],
"out_of_scope": ["Feature Y"]
}