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Task Decomposition

Organization
DevelopersGlobal
task-decomposition

Breaks features into atomic, independently verifiable tasks. No task should take more than 4 hours. Unblocks parallel work and reduces integration risk.

Overview

PublisherDevelopersGlobal
Repositoryai-agent-skills
Skill nametask-decomposition
Stars
212
Forks
33
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 DevelopersGlobal 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.
    https://github.com/DevelopersGlobal/ai-agent-skills/tree/main/skills/task-decomposition
  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/DevelopersGlobal/ai-agent-skills.git /tmp/ai-agent-skills
mkdir -p .claude/skills
cp -r /tmp/ai-agent-skills/skills/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.

Overview

Large tasks fail in large ways. Decomposed tasks fail in small, fixable ways. This skill breaks any feature or project into atomic tasks — each independently implementable, testable, and deployable.

When to Use

  • Before starting any feature that takes more than half a day
  • When a task feels overwhelming or unclear
  • When multiple people need to work in parallel

Process

Step 1: Identify the Deliverable

  1. State what "done" looks like for the whole feature.
  2. List all the things that must be true when it's complete.
  3. Identify dependencies: what must exist before any task can start?

Verify: You can state the full feature goal in 2 sentences.

Step 2: Decompose Into Atomic Tasks

  1. Break the feature into tasks where each task:
    • Can be completed in under 4 hours
    • Has a single, clear output
    • Can be verified independently
    • Can be reverted without breaking other tasks
  2. Each task should be: [verb] [noun] so that [outcome]
    • ✅ "Add rate limiting to /api/login so that brute-force is prevented"
    • ❌ "Work on the login security stuff"

Verify: Every task is under 4 hours. Every task has a clear verify condition.

Step 3: Order and Parallelism

  1. Draw the dependency graph — what blocks what?
  2. Identify tasks that can be done in parallel.
  3. Sequence tasks so integration happens incrementally (not as one big bang at the end).

Verify: The dependency order is clear. No unnecessary sequential dependencies.

Step 4: Estimate and Adjust

  1. For each task, estimate: best case / worst case / expected.
  2. If any task's worst case > 1 day: decompose further.
  3. Total estimate sanity check: does it add up to a reasonable timeline?

Common Rationalizations (and Rebuttals)

ExcuseRebuttal
"I'll figure it out as I go"Decomposition takes 30 minutes. Rework from poor planning takes days.
"It's too complex to break down"Everything can be decomposed. Start with what you know, decompose the rest later.
"The tasks are too granular"Granular tasks ship continuously. Coarse tasks ship never.

Verification

  • Each task is under 4 hours
  • Each task has a single verify condition
  • Dependencies mapped — no circular dependencies
  • Parallel work identified

References

Frequently asked questions

What does the Task Decomposition AI skill do?

Breaks features into atomic, independently verifiable tasks. No task should take more than 4 hours. Unblocks parallel work and reduces integration risk.

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/DevelopersGlobal/ai-agent-skills/tree/main/skills/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 DevelopersGlobal 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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