Task Decomposition logo

Task Decomposition

CommunityPopular
rohitg00
task-decomposition

Breaks down complex software, writing, or research tasks into small, atomic, independently completable units with dependency graphs and milestone breakdowns. Use when the user asks to plan a project, decompose a feature, create subtasks, split up work, or needs help organizing a large piece of work into a step-by-step plan. Triggered by phrases like "break down", "decompose", "where do I start", "too big", "split into tasks", "work breakdown", or "task list".

Overview

Publisherrohitg00
Repositoryskillkit
Skill nametask-decomposition
Stars
1.5K
Forks
147
Bundled files
Instructions only
LicenseApache-2.0
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 rohitg00 on GitHub. Read the source before you install it.

Installation

Install the Task Decomposition 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.
  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/rohitg00/skillkit.git /tmp/skillkit
mkdir -p .claude/skills
cp -r /tmp/skillkit/packages/core/src/methodology/packs/planning/task-decomposition .claude/skills/task-decomposition
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Task Decomposition 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 Task Decomposition 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 Task Decomposition 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.

Task Decomposition

You are breaking down a complex task into smaller, atomic units. Each unit should be independently completable and verifiable.

Core Principle

If a task feels too big, it is too big. Break it down until each piece is obvious.

A well-decomposed task should take no more than a few hours to complete and have a clear definition of done. Aim for tasks that are small, independent, testable, and clearly scoped.

Decomposition Techniques

1. Vertical Slicing

Break by user-visible functionality (each slice is deployable and testable independently):

Feature: User Registration
  Slice 1: Email/password signup — form, validation, account creation
  Slice 2: Email verification — send email, verify link, UI state
  Slice 3: Social login (OAuth) — Google button, OAuth flow, account link

2. Horizontal Layering

Break by system layer:

Feature: Order Processing
  Layer 1: Data Model       — entities, migrations
  Layer 2: Data Access      — repository, CRUD, queries
  Layer 3: Business Logic   — service, validation rules
  Layer 4: API Endpoints    — routes, error handling
  Layer 5: Frontend         — form, API client, loading/error states

3. Workflow Decomposition

Break by process steps:

Task: Checkout flow
  Step 1: Cart validation   — stock check, quantities, totals
  Step 2: Payment           — collect details, validate, process
  Step 3: Order creation    — record, payment link, inventory update
  Step 4: Confirmation      — email, success page, invoice

4. Component Decomposition

Break by UI or system component:

Task: Dashboard page
  Component 1: Header       — logo, nav, user menu
  Component 2: Stats cards  — revenue, orders, customers
  Component 3: Chart        — sales trend, data fetch/transform
  Component 4: Orders table — sort, pagination, row actions

For more detailed worked examples of each technique, see EXAMPLES.md.

Task Template

For each decomposed task, define:

markdown
## Task: [Brief Title]

**Description:**
[What needs to be done in 1-2 sentences]

**Files to Create/Modify:**
- [ ] path/to/file1.ts
- [ ] path/to/file2.ts

**Steps:**
1. [First specific step]
2. [Second specific step]
3. [Third specific step]

**Done When:**
- [ ] [Success criterion 1]
- [ ] [Success criterion 2]
- [ ] Tests pass

**Dependencies:**
- Requires: [Other task if any]
- Blocks: [What this enables]

Dependency Management

Identify Dependencies

Task Graph:

[Data Model] ──┬──▶ [Repository]
               └──▶ [API Types]
[Repository] ──────────▶ [Service]
[API Types] ──────────────────┤
                         [API Endpoints]

Minimize Dependencies

  • Prefer tasks that can run in parallel
  • Use interfaces to decouple dependencies
  • Start with foundational tasks first

Order by Dependencies

Phase 1 (No dependencies):
- Task A: Data model
- Task B: API type definitions
- Task C: UI component skeletons

Phase 2 (Depends on Phase 1):
- Task D: Repository (needs A)
- Task E: API client (needs B)
- Task F: UI logic (needs C)

Phase 3 (Depends on Phase 2):
- Task G: Service (needs D)
- Task H: Connected UI (needs E, F)

Decomposition Checklist

For each task, verify:

  • Atomic? — Can be done without interruption
  • Clear? — Scope is unambiguous
  • Testable? — Know when it's done
  • Independent? — Minimal dependencies
  • Small? — Less than half a day

Integration with Other Skills

  • Use design-first to understand the full scope before decomposing
  • Use verification-gates to define checkpoints between phases
  • Use testing/red-green-refactor to implement each task

Frequently asked questions

What does the Task Decomposition AI skill do?

Breaks down complex software, writing, or research tasks into small, atomic, independently completable units with dependency graphs and milestone breakdowns. Use when the user asks to plan a project, decompose a feature, create subtasks, split up work, or needs help organizing a large piece of work into a step-by-step plan. Triggered by phrases like "break down", "decompose", "where do I start", "too big", "split into tasks", "work breakdown", or "task list".

Why use Task Decomposition on TypingMind?

Because you install it once and use it with any model. Task Decomposition 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 Task Decomposition in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/rohitg00/skillkit/tree/main/packages/core/src/methodology/packs/planning/task-decomposition. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Task Decomposition?

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 Task Decomposition?

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

Is the Task Decomposition AI skill free?

Yes. It is published on GitHub by rohitg00 under the Apache-2.0 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇