How do I refine a generated specification?

You can add feedback directly into the tags within the spec file and run the /spec command again; the skill will process your comments and update the task list accordingly.

Can I use this for an existing project, or is it only for new ones?

It is designed for both. The skill includes a context section specifically for researching existing codebase patterns and integration points to ensure new tasks are consistent with your current architecture.

What is the primary purpose of the Spec Generation skill?

It creates a structured 'blueprint' for development tasks, ensuring that Claude has a clear, machine-parseable roadmap to follow when implementing new features or projects.

Why does this skill use XML-like tags inside Markdown?

This hybrid format allows the specification to be easily read and edited by humans in any text editor while providing strict markers that Claude can use for automated processing and task 'pouring'.

Spec Generation for Choo Choo Ralph

Name: Spec Generation for Choo Choo Ralph
Author: mj-meyer

bymj-meyer

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生产力与工作流

Generates structured, machine-parseable workflow specifications for Claude Code development loops.

关于

The Spec Generation skill provides a standardized framework for breaking down complex software projects into actionable, verifiable tasks within the Choo Choo Ralph ecosystem. By utilizing a hybrid format of YAML frontmatter and XML-like Markdown tags, it enables Claude to create human-readable specifications that capture codebase context, integration points, and success criteria. This skill is essential for developers looking to maintain architectural consistency and automate the transition from high-level requirements to granular implementation steps.

主要功能

9 GitHub stars
Context-aware research of existing codebase patterns and integration points
Scalable architecture supporting both single features and full-scale applications
Standardized YAML frontmatter for automated project metadata tracking
Integrated test step definitions to ensure high-level feature verification
Iterative refinement workflow using built-in review tags for human feedback

使用场景

Documenting implementation paths for complex features in existing codebases
Standardizing team-wide workflows for AI-assisted software development
Generating a comprehensive task breakdown for greenfield software projects

关于

主要功能

9 GitHub stars
Context-aware research of existing codebase patterns and integration points
Scalable architecture supporting both single features and full-scale applications
Standardized YAML frontmatter for automated project metadata tracking
Integrated test step definitions to ensure high-level feature verification
Iterative refinement workflow using built-in review tags for human feedback

使用场景

Documenting implementation paths for complex features in existing codebases
Standardizing team-wide workflows for AI-assisted software development
Generating a comprehensive task breakdown for greenfield software projects