Skip to content
All Skills

Structured Autonomy Plan

Structured Autonomy Planning Prompt

Software Engineering|v1|Updated 7/14/2026|GitHub source
MCP get_skill({ skillId: "feature-name-934e47cc" })

Use this skill with your agent

Create a free account and connect via MCP

Get Started Free
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-copilot#planning

Related Skills

More skills in Software Engineering

Accessibility Standards

Comprehensive web accessibility standards based on WCAG 2.2 AA, with 38+ anti-patterns, legal enforcement context (EAA, ADA Title II), WAI-ARIA patterns, and framework-specific fixes for modern web frameworks and libraries.

#github-copilot#accessibilityMIT

Accord

Authoring unified specification packages across Business/Development/Design teams via staged elaboration (L0 Vision → L1 Requirements → L2 Team Detail → L3 Acceptance Criteria). No code. Use when authoring cross-team specs, building L0-L3 packages, or aligning Biz/Dev/Design on a single source of truth.

#broad-capability#developmentMIT

Acquire Codebase Knowledge

Use this skill when the user explicitly asks to map, document, or onboard into an existing codebase. Trigger for prompts like "map this codebase", "document this architecture", "onboard me to this repo", or "create codebase docs". Do not trigger for routine feature implementation, bug fixes, or narrow code edits unless the user asks for repository-level discovery.

#github-copilot#documentationMIT

Acreadiness Assess

Run the AgentRC readiness assessment on the current repository and produce a static HTML dashboard at reports/index.html. Wraps `npx github:microsoft/agentrc readiness` and hands off rendering to the @ai-readiness-reporter custom agent. Supports policies (--policy) for org-specific scoring. Use when asked to assess, audit, or score the AI readiness of a repo.

#github-copilot#planningMIT

Acreadiness Generate Instructions

Generate tailored AI agent instruction files via AgentRC instructions command. Produces .github/copilot-instructions.md (default, recommended for Copilot in VS Code) plus optional per-area .instructions.md files with applyTo globs for monorepos. Use after running /acreadiness-assess to close gaps in the AI Tooling pillar.

#github-copilot#skillMIT

Acreadiness Policy

Help the user pick, write, or apply an AgentRC policy. Policies customise readiness scoring by disabling irrelevant checks, overriding impact/level, setting pass-rate thresholds, or chaining org baselines with team overrides. Use when the user asks about strict mode, AI-only scoring, custom weights, CI gating, or wants org-wide standardisation.

#github-copilot#planningMIT