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Breakdown Feature Implementation

OrganizationPopular
github
breakdown-feature-implementation

Prompt for creating detailed feature implementation plans, following Epoch monorepo structure.

Overview

Publishergithub
Repositoryawesome-copilot
Skill namebreakdown-feature-implementation
Stars
39.6K
Forks
5K
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by github on GitHub. Read the source before you install it.

Installation

Install the Breakdown Feature Implementation AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/github/awesome-copilot/tree/main/skills/breakdown-feature-implementation
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/github/awesome-copilot.git /tmp/awesome-copilot
mkdir -p .claude/skills
cp -r /tmp/awesome-copilot/skills/breakdown-feature-implementation .claude/skills/breakdown-feature-implementation
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Breakdown Feature Implementation in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Breakdown Feature Implementation on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Breakdown Feature Implementation is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Feature Implementation Plan Prompt

Goal

Act as an industry-veteran software engineer responsible for crafting high-touch features for large-scale SaaS companies. Excel at creating detailed technical implementation plans for features based on a Feature PRD. Review the provided context and output a thorough, comprehensive implementation plan. Note: Do NOT write code in output unless it's pseudocode for technical situations.

Output Format

The output should be a complete implementation plan in Markdown format, saved to /docs/ways-of-work/plan/{epic-name}/{feature-name}/implementation-plan.md.

File System

Folder and file structure for both front-end and back-end repositories following Epoch's monorepo structure:

apps/
  [app-name]/
services/
  [service-name]/
packages/
  [package-name]/

Implementation Plan

For each feature:

Goal

Feature goal described (3-5 sentences)

Requirements
  • Detailed feature requirements (bulleted list)
  • Implementation plan specifics
Technical Considerations
System Architecture Overview

Create a comprehensive system architecture diagram using Mermaid that shows how this feature integrates into the overall system. The diagram should include:

  • Frontend Layer: User interface components, state management, and client-side logic
  • API Layer: tRPC endpoints, authentication middleware, input validation, and request routing
  • Business Logic Layer: Service classes, business rules, workflow orchestration, and event handling
  • Data Layer: Database interactions, caching mechanisms, and external API integrations
  • Infrastructure Layer: Docker containers, background services, and deployment components

Use subgraphs to organize these layers clearly. Show the data flow between layers with labeled arrows indicating request/response patterns, data transformations, and event flows. Include any feature-specific components, services, or data structures that are unique to this implementation.

  • Technology Stack Selection: Document choice rationale for each layer
  • Integration Points: Define clear boundaries and communication protocols
  • Deployment Architecture: Docker containerization strategy
  • Scalability Considerations: Horizontal and vertical scaling approaches
Database Schema Design

Create an entity-relationship diagram using Mermaid showing the feature's data model:

  • Table Specifications: Detailed field definitions with types and constraints
  • Indexing Strategy: Performance-critical indexes and their rationale
  • Foreign Key Relationships: Data integrity and referential constraints
  • Database Migration Strategy: Version control and deployment approach
API Design
  • Endpoints with full specifications
  • Request/response formats with TypeScript types
  • Authentication and authorization with Stack Auth
  • Error handling strategies and status codes
  • Rate limiting and caching strategies
Frontend Architecture
Component Hierarchy Documentation

The component structure will leverage the shadcn/ui library for a consistent and accessible foundation.

Layout Structure:

Recipe Library Page
├── Header Section (shadcn: Card)
│   ├── Title (shadcn: Typography `h1`)
│   ├── Add Recipe Button (shadcn: Button with DropdownMenu)
│   │   ├── Manual Entry (DropdownMenuItem)
│   │   ├── Import from URL (DropdownMenuItem)
│   │   └── Import from PDF (DropdownMenuItem)
│   └── Search Input (shadcn: Input with icon)
├── Main Content Area (flex container)
│   ├── Filter Sidebar (aside)
│   │   ├── Filter Title (shadcn: Typography `h4`)
│   │   ├── Category Filters (shadcn: Checkbox group)
│   │   ├── Cuisine Filters (shadcn: Checkbox group)
│   │   └── Difficulty Filters (shadcn: RadioGroup)
│   └── Recipe Grid (main)
│       └── Recipe Card (shadcn: Card)
│           ├── Recipe Image (img)
│           ├── Recipe Title (shadcn: Typography `h3`)
│           ├── Recipe Tags (shadcn: Badge)
│           └── Quick Actions (shadcn: Button - View, Edit)
  • State Flow Diagram: Component state management using Mermaid
  • Reusable component library specifications
  • State management patterns with Zustand/React Query
  • TypeScript interfaces and types
Security Performance
  • Authentication/authorization requirements
  • Data validation and sanitization
  • Performance optimization strategies
  • Caching mechanisms

Context Template

  • Feature PRD: [The content of the Feature PRD markdown file]

Frequently asked questions

What does the Breakdown Feature Implementation AI skill do?

Prompt for creating detailed feature implementation plans, following Epoch monorepo structure.

Why use Breakdown Feature Implementation on TypingMind?

Because you install it once and use it with any model. Breakdown Feature Implementation is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Breakdown Feature Implementation in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/github/awesome-copilot/tree/main/skills/breakdown-feature-implementation. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Breakdown Feature Implementation?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Breakdown Feature Implementation?

As many as you like. As long as a model supports skills, you can use Breakdown Feature Implementation with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Breakdown Feature Implementation AI skill free?

Yes. It is published on GitHub by github under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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