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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.
// 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.
| name | code-task-generator |
| description | 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. |
| type | anthropic-skill |
| version | 1.1 |
| metadata | {"internal":true} |
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.
These rules apply across ALL steps:
specs/{task_name}/tasks/): Output directory for code task filesConstraints:
Check if input is a file with PDD plan structure (checklist + numbered steps). Set mode to "pdd" or "description" and inform the user.
For both modes: create measurable acceptance criteria in Given-When-Then format and prepare a task breakdown plan.
Present the proposed breakdown to the user:
Create files following the Code Task Format below.
PDD mode specifics:
step{NN}/ folder (zero-padded: step01, step02, step10)task-01-{title}.code-task.md, task-02-{title}.code-task.mdAll tasks:
status: pending, created: YYYY-MM-DD, started: null, completed: null.code-task.md extensionList 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.
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:
ralph run --config presets/pdd-to-code-assist.ymlralph run -c ralph.yml -H builtin:code-assistEach code task file MUST follow this structure:
---
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: 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]
Description mode input: "I need a function that validates email addresses and returns detailed error messages"
Description mode output: specs/email-validator/tasks/email-validator.code-task.md — task with acceptance criteria for valid/invalid email handling, error messages, and unit tests.
PDD mode input: "specs/data-pipeline/plan.md"
PDD mode output: specs/data-pipeline/tasks/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.
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.
Introspect, explain, and improve Ralph Orchestrator using its published llms.txt doc map. Use this skill whenever the user asks questions about Ralph's behavior, wants to understand how a Ralph internal works (event loop, hats, memories, tasks, backends, presets), debug an unfamiliar failure mode, or propose a code change to the ralph-orchestrator repo. The skill teaches the agent to discover authoritative answers from the live docs via llms.txt before guessing, and to scope improvements through the published architecture rather than the local checkout alone.
Run, monitor, resume, merge, and debug Ralph loops. Use this skill whenever the user asks to operate `ralph run` or `ralph loops`, inspect loop state, recover suspended loops, analyze diagnostics, or unblock merge queue issues.
Guides implementation of code tasks using test-driven development in an Explore, Plan, Code, Commit workflow. Acts as a Technical Implementation Partner and TDD Coach — following existing patterns, avoiding over-engineering, and producing idiomatic, modern code.
Use when testing Ralph's hat collection presets, validating preset configurations, or auditing the preset library for bugs and UX issues.
Lists all code tasks in the repository with their status, dates, and metadata. Useful for getting an overview of pending work or finding specific tasks.
Transforms a rough idea into a detailed design document with implementation plan. Follows Prompt-Driven Development — iterative requirements clarification, research, design, and planning.