MR
Mayur Rathi
@github
⭐ 34.1k GitHub stars

Structured-Autonomy-Plan

Structured-Autonomy-Plan是一款code方向的AI技能,核心价值是Structured Autonomy Planning Prompt,可用于解决开发者在code领域的实际问题,帮助用户提升效率、自动化重复任务或优化工作流。

Structured Autonomy Planning Prompt

Last verified on: 2026-05-30
mkdir -p ./skills/structured-autonomy-plan && curl -sfL https://raw.githubusercontent.com/github/awesome-copilot/main/skills/structured-autonomy-plan/SKILL.md -o ./skills/structured-autonomy-plan/SKILL.md

Run in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).

Skill Content

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>

🎯 Best For

  • Claude users
  • GitHub Copilot users
  • Software engineers
  • Development teams
  • Tech leads

💡 Use Cases

  • Code quality improvement
  • Best practice enforcement

📖 How to Use This Skill

  1. 1

    Install the Skill

    Copy the install command from the Terminal tab and run it. The SKILL.md file downloads to your local skills directory.

  2. 2

    Load into Your AI Assistant

    Open Claude or GitHub Copilot and reference the skill. Paste the SKILL.md content or use the system prompt tab.

  3. 3

    Apply Structured-Autonomy-Plan to Your Work

    Open your project in the AI assistant and ask it to apply the skill. Start with a small module to verify the output quality.

  4. 4

    Review and Refine

    Review AI suggestions before committing. Run tests, check for regressions, and iterate on the skill output.

❓ Frequently Asked Questions

Is Structured-Autonomy-Plan compatible with Cursor and VS Code?

Yes — this skill works with any AI coding assistant including Cursor, VS Code with Copilot, and JetBrains IDEs.

Do I need specific dependencies for Structured-Autonomy-Plan?

Check the install command and Works With section. Most code skills only require the AI assistant and your codebase.

How do I install Structured-Autonomy-Plan?

Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/structured-autonomy-plan/SKILL.md, ready to use.

Can I customize this skill for my team?

Absolutely. Edit the SKILL.md file to add team-specific instructions, examples, or workflows.

⚠️ Common Mistakes to Avoid

Skipping validation

Always test AI-generated code changes, even for simple refactors.

Missing dependency updates

Check if the skill requires updated dependencies or new packages.

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