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Code Task Generator

CommunityPopular
mikeyobrien
code-task-generator

Generates structured .code-task.md files from descriptions or PDD implementation plans. Auto-detects input type, creates properly formatted tasks with Given-When-Then acceptance criteria.

Overview

Publishermikeyobrien
Repositoryralph-orchestrator
Skill namecode-task-generator
Stars
3.2K
Forks
299
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 mikeyobrien on GitHub. Read the source before you install it.

Installation

Install the Code Task Generator 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/mikeyobrien/ralph-orchestrator/tree/main/.claude/skills/code-task-generator
  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/mikeyobrien/ralph-orchestrator.git /tmp/ralph-orchestrator
mkdir -p .claude/skills
cp -r /tmp/ralph-orchestrator/.claude/skills/code-task-generator .claude/skills/code-task-generator
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Code Task Generator 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 Code Task Generator 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 Code Task Generator 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.

Code Task Generator

Overview

Generate structured code task files from rough descriptions or PDD implementation plans. Auto-detects input type and creates properly formatted .code-task.md files. For PDD plans, processes one step at a time to allow learning between steps.

Important Notes

These rules apply across ALL steps:

  • User approval required: Present the task breakdown plan and get explicit approval before generating any files.
  • Tests are integrated: Include unit test requirements in each task's acceptance criteria. Never create separate "add tests" tasks.
  • PDD mode references: Always include the design document path as required reading. Only include research docs if directly relevant to the specific task.

Parameters

  • input (required): Task description, file path, or PDD plan path
  • step_number (optional, PDD only): Specific step to process. Auto-determines next uncompleted step if omitted.
  • output_dir (optional, default: .ralph/tasks/): Output directory for code task files
  • task_name (optional, description mode only): Override auto-generated task name

Constraints:

  • You MUST ask for all required parameters upfront in a single prompt
  • You MUST support input as: direct text, file path, directory path (looks for plan.md), or URL

Steps

1. Detect Input Mode

Check if input is a file with PDD plan structure (checklist + numbered steps). Set mode to "pdd" or "description" and inform the user.

2. Analyze Input

  • PDD mode: Parse the plan, extract steps and checklist status, determine target step (from step_number or first uncompleted)
  • Description mode: Identify core functionality, technical requirements, complexity level (Low/Medium/High), and technology domain

3. Structure Requirements

  • PDD mode: Extract the target step's title, description, demo requirements, constraints, and integration notes with previous steps. Identify relevant research documents.
  • Description mode: Identify functional requirements, infer technical constraints and dependencies.

For both modes: create measurable acceptance criteria in Given-When-Then format and prepare a task breakdown plan.

4. Plan Tasks

Present the proposed breakdown to the user:

  • One-line summary per task
  • Proposed sequence and dependencies
  • You MUST NOT generate files until the user explicitly approves

5. Generate Tasks

Create files following the Code Task Format below.

PDD mode specifics:

  • Create .ralph/tasks/{task_name}/step{NN}/ folder by default (zero-padded: step01, step02, step10)
  • Name files sequentially: task-01-{title}.code-task.md, task-02-{title}.code-task.md
  • Break down by functional components, not testing phases

All tasks:

  • You MUST use the exact Code Task Format structure below
  • You MUST include YAML frontmatter with status: pending, created: YYYY-MM-DD, started: null, completed: null
  • You MUST use kebab-case names with .code-task.md extension
  • You MUST include acceptance criteria covering main functionality and unit tests

6. Report Results

List generated files with paths. For PDD mode, include the step's demo requirements. Suggest running code-assist on tasks in sequence, or using Ralph for autonomous implementation.

7. Offer Ralph Integration

Ask: "Would you like me to set up Ralph to implement these tasks autonomously?"

If yes, create a concise PROMPT.md with objective, spec directory reference, execution order, and acceptance criteria. Suggest the appropriate command:

  • Full pipeline: ralph run --config presets/pdd-to-code-assist.yml
  • Simpler flow: ralph run -c ralph.yml -H builtin:code-assist

Code Task Format Specification

Each code task file MUST follow this structure:

markdown
---
status: pending
created: YYYY-MM-DD
started: null
completed: null
---
# Task: [Task Name]

## Description
[What needs to be implemented and why]

## Background
[Context needed to understand the task]

## Reference Documentation
**Required:**
- Design: .ralph/specs/{task_name}/design.md

**Additional References (if relevant to this task):**
- [Specific research document or section]

**Note:** Read the design document before beginning implementation.

## Technical Requirements
1. [First requirement]
2. [Second requirement]

## Dependencies
- [Dependency with details]

## Implementation Approach
1. [Implementation step or approach]

## Acceptance Criteria

1. **[Criterion Name]**
   - Given [precondition]
   - When [action]
   - Then [expected result]

## Metadata
- **Complexity**: [Low/Medium/High]
- **Labels**: [Comma-separated labels]
- **Required Skills**: [Skills needed]

Examples

Description mode input: "I need a function that validates email addresses and returns detailed error messages"

Description mode output: .ralph/tasks/email-validator.code-task.md — task with acceptance criteria for valid/invalid email handling, error messages, and unit tests.

PDD mode input: ".ralph/specs/data-pipeline/plan.md"

PDD mode output: .ralph/tasks/data-pipeline/step02/ containing task-01-create-data-models.code-task.md, task-02-implement-validation.code-task.md, task-03-add-serialization.code-task.md — each with design.md reference, acceptance criteria, and demo requirements.

Troubleshooting

Vague description: Ask clarifying questions, suggest common patterns, create a basic task and offer to refine.

Complex description: Suggest breaking into smaller tasks, focus on core functionality first, offer to create related tasks.

Missing technical details: Make reasonable assumptions, include multiple approaches, note areas needing user decisions.

Plan file not found: Check if path is a directory (look for plan.md within), suggest common PDD plan locations.

Invalid plan format: Identify missing sections, suggest running PDD to generate a proper plan, extract what's available.

All steps complete: Inform user, ask if they want a specific step anyway, suggest reviewing for new steps.

Frequently asked questions

What does the Code Task Generator AI skill do?

Generates structured .code-task.md files from descriptions or PDD implementation plans. Auto-detects input type, creates properly formatted tasks with Given-When-Then acceptance criteria.

Why use Code Task Generator on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/mikeyobrien/ralph-orchestrator/tree/main/.claude/skills/code-task-generator. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Code Task Generator?

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 Code Task Generator?

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

Is the Code Task Generator AI skill free?

Yes. It is published on GitHub by mikeyobrien 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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