structured-autonomy-plan — GitHub Copilot skill
This skill plans development work before code is written. It researches the repository, splits work into commits, and pauses for clarification before implementation.
npx skills add github/awesome-copilot --skill structured-autonomy-planWhat structured-autonomy-plan does
structured-autonomy-plan acts as a planning agent. It first asks a subagent to inspect related code, documentation, dependencies, and existing patterns, then turns the request into testable commits. A simple feature gets one commit; a complex request is split into several.
The skill saves its output to plans/{feature-name}/plan.md. The plan records a branch, goal, affected files, proposed changes, and testing for each step. Open questions receive [NEEDS CLARIFICATION] markers, after which the agent waits for feedback.
This skill is for planning, not implementation, so it does not write the requested code. Install it when a PR needs a clear implementation route; for a tiny edit, the process can be unnecessary.
What it helps with
- research related code before planning a feature
- split a complex request into testable commits
- write a plan to
plans/{feature-name}/plan.md - surface missing decisions before implementation
Example prompts for the agent
- Create a plan for this feature and research the related parts of the repository first.
- Break this request into commits for one PR and list the affected files.
- Save the plan in `plans/{feature-name}/plan.md` and flag anything that needs clarification.
How to install structured-autonomy-plan
1Skills CLI (Vercel)
npx skills add github/awesome-copilot --skill structured-autonomy-plan2GitHub CLI
gh skill install github/awesome-copilot structured-autonomy-plan3Manually: put the files in place
.github/skills/structured-autonomy-plan/SKILL.md1Skills CLI (Vercel)
npx skills add github/awesome-copilot --skill structured-autonomy-plan -a claude-code2Manually: put the files in place
~/.claude/skills/structured-autonomy-plan/SKILL.mdCopy the whole skill folder; for one project use .claude/skills/structured-autonomy-plan/
Manually: put the files in place
.agents/skills/structured-autonomy-plan/SKILL.mdFor all projects use ~/.agents/skills/
Manually: put the files in place
.cursor/skills/structured-autonomy-plan/SKILL.mdCursor also reads .agents/skills/ and .claude/skills/
Platform CLI
gemini skills install https://github.com/github/awesome-copilot --path skills/structured-autonomy-planManually: put the files in place
.devin/skills/structured-autonomy-plan/SKILL.mdThe legacy .windsurf/skills/ path still works
Claude.ai
Zip the folder and upload it in Settings → Capabilities → Skills
From the same set554
The whole set →Similar
Questions about structured-autonomy-plan
How do I install structured-autonomy-plan in GitHub Copilot?
Run npx skills add github/awesome-copilot --skill structured-autonomy-plan. You can also use gh skill install github/awesome-copilot structured-autonomy-plan.
What does structured-autonomy-plan do?
It researches the task context and writes a development plan without writing code. The work is organized as commits for one PR on a dedicated branch.
Where does structured-autonomy-plan save the plan?
It writes the result to plans/{feature-name}/plan.md. The template includes the goal, branch, implementation steps, files, and testing notes.
Source text
SKILL.md · MIT
---
name: structured-autonomy-plan
description: 'Structured Autonomy Planning Prompt'
---
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.
<workflow>
## Step 1: Research and Gather Context
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.
## Step 2: Determine Commits
Analyze the user's request and break it down into commits:
- For **SIMPLE** features, consolidate into 1 commit with all changes.
- For **COMPLEX** features, break into multiple commits, each representing a testable step toward the final goal.
## Step 3: Plan Generation
1. Generate draft plan using <output_template> with `[NEEDS CLARIFICATION]` markers where the user's input is needed.
2. Save the plan to "plans/{feature-name}/plan.md"
4. Ask clarifying questions for any `[NEEDS CLARIFICATION]` sections
5. MANDATORY: Pause for feedback
6. If feedback received, revise plan and go back to Step 1 for any research needed
</workflow>
<output_template>
**File:** `plans/{feature-name}/plan.md`
```markdown
# {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:
1. **Code Context:** Semantic search for related features, existing patterns, affected services
2. **Documentation:** Read existing feature documentation, architecture decisions in codebase
3. **Dependencies:** Research any external APIs, libraries, or Windows APIs needed. Use #context7 if available to read relevant documentation. ALWAYS READ THE DOCUMENTATION FIRST.
4. **Patterns:** Identify how similar features are implemented in ResizeMe
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>
© github · MIT · github/awesome-copilot