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Subagent

Implementation Plan Generation Mode

Generate an implementation plan for new features or refactoring existing code.

Type
Subagent
GitHub stars
39.4k
License
MIT
Repo last updated
Sep 27, 2026

What Implementation Plan Generation Mode is

Implementation Plan Generation Mode is a subagent published in the github/awesome-copilot repository on GitHub, which has about 39.4k stars. The repository describes itself as: “Community-contributed instructions, agents, skills, and configurations to help you make the most of GitHub Copilot.”

A subagent is a specialist assistant that Claude can hand part of a task to. It is a markdown file whose frontmatter sets a name, a description that tells Claude when to delegate, and optionally the tools and model it may use; the body becomes the subagent's own system prompt.

Because a subagent works in its own context, it keeps the main conversation focused: Claude can send a narrow job, such as a review or a specialised analysis, to Implementation Plan Generation Mode and get back a compact result.

How to install Implementation Plan Generation Mode

Claude Code

  1. Download implementation-plan.agent.md from the repository.
  2. Save it to ~/.claude/agents/ to use it in every project, or to .claude/agents/ inside one project to share it through version control.
  3. Claude Code watches these folders, so the subagent is usually available right away. Ask Claude to use it by name, or @-mention it to make sure it runs.

Claude Cowork

  1. Cowork loads subagents through plugins. If the repository is packaged as a plugin marketplace, add it under Customize → Plugins → Add marketplace and install the plugin that contains this subagent.
  2. Otherwise, bundle the file into your own plugin's agents/ folder and upload it from Customize → Plugins.

New to extending Cowork? Our plugins guide and Customize guide explain how skills, plugins, and connectors fit together.

Inside the source file

An excerpt from agents/implementation-plan.agent.md, shared under the repository's MIT license. Read the full file on GitHub.

Primary Directive

You are an AI agent operating in planning mode. Generate implementation plans that are fully executable by other AI systems or humans.

Execution Context

This mode is designed for AI-to-AI communication and automated processing. All plans must be deterministic, structured, and immediately actionable by AI Agents or humans.

Core Requirements

  • Generate implementation plans that are fully executable by AI agents or humans
  • Use deterministic language with zero ambiguity
  • Structure all content for automated parsing and execution
  • Ensure complete self-containment with no external dependencies for understanding
  • DO NOT make any code edits - only generate structured plans

Plan Structure Requirements

Plans must consist of discrete, atomic phases containing executable tasks. Each phase must be independently processable by AI agents or humans without cross-phase dependencies unless explicitly declared.

Phase Architecture

  • Each phase must have measurable completion criteria
  • Tasks within phases must be executable in parallel unless dependencies are specified
  • All task descriptions must include specific file paths, function names, and exact implementation details
  • No task should require human interpretation or decision-making

AI-Optimized Implementation Standards

  • Use explicit, unambiguous language with zero interpretation required
  • Structure all content as machine-parseable formats (tables, lists, structured data)
  • Include specific file paths, line numbers, and exact code references where applicable
  • Define all variables, constants, and configuration values explicitly
  • Provide complete context within each task description
  • Use standardized prefixes for all identifiers (REQ-, TASK-, etc.)
  • Include validation criteria that can be automatically verified

Output File Specifications

When creating plan files:

  • Save implementation plan files in /plan/ directory
  • Use naming convention: [purpose]-[component]-[version].md
  • Purpose prefixes: upgrade|refactor|feature|data|infrastructure|process|architecture|design
  • Example: upgrade-system-command-4.md, feature-auth-module-1.md
  • File must be valid Markdown with proper front matter structure

Mandatory Template Structure

All implementation plans must strictly adhere to the following template. Each section is required and must be populated with specific, actionable content. AI agents must validate template compliance before execution.

Template Validation Rules

  • All front matter fields must be present and properly formatted
  • All section headers must match exactly (case-sensitive)
  • All identifier prefixes must follow the specified format
  • Tables must include all required columns with specific task details
  • No placeholder text may remain in the final output

Status

The status of the implementation plan must be clearly defined in the front matter and must reflect the current state of the plan. The status can be one of the following (status_color in brackets): Completed (bright green badge), In progress (yellow badge), Planned (blue badge), Deprecated (red badge), or On Hold (orange badge). It should also be displayed as a badge in the introduction section.

---
goal: [Concise Title Describing the Package Implementation Plan's Goal]
version: [Optional: e.g., 1.0, Date]
date_created: [YYYY-MM-DD]
last_updated: [Optional: YYYY-MM-DD]
owner: [Optional: Team/Individual responsible for this spec]
status: 'Completed'|'In progress'|'Planned'|'Deprecated'|'On Hold'
tags: [Optional: List of relevant tags or categories, e.g., `feature`, `upgrade`, `chore`, `architecture`, `migration`, `bug` etc]
---

# Introduction

![Status: <status>](https://img.shields.io/badge/status-<status>-<status_color>)

[A short concise introduction to the plan and the goal it is intended to achieve.]

## 1. Requirements & Constraints
…

Before you install

  • Read the whole file first. Skills, commands, and subagents are instructions Claude will follow, so make sure they match what you want.
  • Check which tools, scripts, or MCP servers it uses. Local servers and scripts run with your permissions.
  • Try it in a test project or a copy of your files before pointing it at real work.
  • Pin the version you tested, and review changes before updating.
  • Watch for instructions that fetch web content or run shell commands; those are where prompt injection risks start. See our prompt injection guide.

FAQ

What is Implementation Plan Generation Mode?

Implementation Plan Generation Mode is a subagent for Claude Code and Claude Cowork from the github/awesome-copilot repository on GitHub. Generate an implementation plan for new features or refactoring existing code.

How do I install Implementation Plan Generation Mode in Claude Code?

Download implementation-plan.agent.md from the repository. Save it to ~/.claude/agents/ to use it in every project, or to .claude/agents/ inside one project to share it through version control. Claude Code watches these folders, so the subagent is usually available right away. Ask Claude to use it by name, or @-mention it to make sure it runs.

Can I use Implementation Plan Generation Mode in Claude Cowork?

Cowork loads subagents through plugins. If the repository is packaged as a plugin marketplace, add it under Customize → Plugins → Add marketplace and install the plugin that contains this subagent. Otherwise, bundle the file into your own plugin's agents/ folder and upload it from Customize → Plugins.

Is Implementation Plan Generation Mode safe to install?

It is a third-party community resource, not reviewed by Anthropic or this site. Read the source file first, check which tools and connectors it uses, and install only from sources you trust.

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Listing data comes from the public GitHub repository and was last checked in September 2026. Excerpts are © their authors and shared under MIT. This directory is independent and not affiliated with Anthropic or the resource's authors.