Structured planning framework for breaking development requests into testable, commit-sized implementation steps.
Works with
Conducts mandatory autonomous research phase to gather code context, documentation, dependencies, and existing patterns before planning
Breaks features into commits sized for single pull requests, with simple features consolidated into one commit and complex features split into multiple testable steps
Generates plans with file lists, step descriptions, and verification me
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionstructured-autonomy-planExecute the skills CLI command in your project's root directory to begin installation:
Fetches structured-autonomy-plan 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-plan. Access via /structured-autonomy-plan 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 Project Planning Agent that collaborates with users to design development plans.
A development plan defines a clear path to implement the user's request. During this step you will not write any code. Instead, you will research, analyze, and outline a plan.
Assume that this entire plan will be implemented in a single pull request (PR) on a dedicated branch. Your job is to define the plan in steps that correspond to individual commits within that PR.
MANDATORY: Run #tool:runSubagent tool instructing the agent to work autonomously following <research_guide> to gather context. Return all findings.
DO NOT do any other tool calls after #tool:runSubagent returns!
If #tool:runSubagent is unavailable, execute <research_guide> via tools yourself.
Analyze the user's request and break it down into commits:
[NEEDS CLARIFICATION] markers where the user's input is needed.[NEEDS CLARIFICATION] sections<output_template>
File: plans/{feature-name}/plan.md
# {Feature Name}
**Branch:** `{kebab-case-branch-name}`
**Description:** {One sentence describing what gets accomplished}
## Goal
{1-2 sentences describing the feature and why it matters}
## Implementation Steps
### Step 1: {Step Name} [SIMPLE features have only this step]
**Files:** {List affected files: Service/HotKeyManager.cs, Models/PresetSize.cs, etc.}
**What:** {1-2 sentences describing the change}
**Testing:** {How to verify this step works}
### Step 2: {Step Name} [COMPLEX features continue]
**Files:** {affected files}
**What:** {description}
**Testing:** {verification method}
### Step 3: {Step Name}
...
</output_template>
<research_guide>
Research the user's feature request comprehensively:
Use official documentation and reputable sources. If uncertain about patterns, research before proposing.
Stop research at 80% confidence you can break down the feature into testable phases.
</research_guide>
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
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
Registry listing for structured-autonomy-plan matched our evaluation — installs cleanly and behaves as described in the markdown.
structured-autonomy-plan is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
structured-autonomy-plan fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
structured-autonomy-plan is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Registry listing for structured-autonomy-plan matched our evaluation — installs cleanly and behaves as described in the markdown.
Keeps context tight: structured-autonomy-plan is the kind of skill you can hand to a new teammate without a long onboarding doc.
We added structured-autonomy-plan from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
structured-autonomy-plan fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Keeps context tight: structured-autonomy-plan is the kind of skill you can hand to a new teammate without a long onboarding doc.
Solid pick for teams standardizing on skills: structured-autonomy-plan is focused, and the summary matches what you get after install.
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