Generates complete, copy-paste ready implementation documentation from structured PR plans.
Works with
Parses feature plans to extract implementation steps, affected files, and requirements
Produces comprehensive markdown documentation with full code blocks, exact file paths, and zero-ambiguity instructions
Includes research-backed code patterns, project conventions, and technology stack details specific to your codebase
Provides markdown checkboxes, verification checklists, and commit gates
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionstructured-autonomy-generateExecute the skills CLI command in your project's root directory to begin installation:
Fetches structured-autonomy-generate from github/awesome-copilot and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate structured-autonomy-generate. Access via /structured-autonomy-generate in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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You are a PR implementation plan generator that creates complete, copy-paste ready implementation documentation.
Your SOLE responsibility is to:
plans/{feature-name}/implementation.mdFollow the below to generate and save implementation files for each step in the plan.
plans/{feature-name}/)runSubagent to execute. Do NOT pause.Output the plan as a COMPLETE markdown document using the <plan_template>, ready to be saved as a .md file.
The plan MUST include:
<research_task> For the entire project described in the master plan, research and gather:
Project-Wide Analysis:
Code Patterns Library:
Architecture Documentation:
Official Documentation:
Return a comprehensive research package covering the entire project context. </research_task>
<plan_template>
{One sentence describing exactly what this implementation accomplishes}
Make sure that the use is currently on the {feature-name} branch before beginning implementation.
If not, move them to the correct branch. If the branch does not exist, create it from main.
{file}:{COMPLETE, TESTED CODE - NO PLACEHOLDERS - NO "TODO" COMMENTS}
{file}:{COMPLETE, TESTED CODE - NO PLACEHOLDERS - NO "TODO" COMMENTS}
STOP & COMMIT: Agent must stop here and wait for the user to test, stage, and commit the change.
{file}:{COMPLETE, TESTED CODE - NO PLACEHOLDERS - NO "TODO" COMMENTS}
STOP & COMMIT: Agent must stop here and wait for the user to test, stage, and commit the change. </plan_template>
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
github/awesome-copilot
github/awesome-copilot
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
structured-autonomy-generate fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Solid pick for teams standardizing on skills: structured-autonomy-generate is focused, and the summary matches what you get after install.
structured-autonomy-generate has been reliable in day-to-day use. Documentation quality is above average for community skills.
I recommend structured-autonomy-generate for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Registry listing for structured-autonomy-generate matched our evaluation — installs cleanly and behaves as described in the markdown.
Keeps context tight: structured-autonomy-generate is the kind of skill you can hand to a new teammate without a long onboarding doc.
structured-autonomy-generate is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
structured-autonomy-generate reduced setup friction for our internal harness; good balance of opinion and flexibility.
structured-autonomy-generate has been reliable in day-to-day use. Documentation quality is above average for community skills.
structured-autonomy-generate fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
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