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code-task-generator代码任务生成器

Agent Skill

code-task-generator 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

897

周安装

37

GitHub Stars

2,830

下载量

293
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

3

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:code-task-generator(代码任务生成器)
来源仓库:https://github.com/mikeyobrien/ralph-orchestrator
仓库路径:skills/code-task-generator
安装命令:
npx skills add https://github.com/mikeyobrien/ralph-orchestrator --skill code-task-generator
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/mikeyobrien/ralph-orchestrator --skill code-task-generator

简介

用于将粗略描述或 PDD 转化为结构化任务文件。

  • 自动识别输入类型并生成 .code-task.md。
  • 每步需用户批准后再继续,避免失控迭代。
  • 集成单元测试要求于接受标准中。code-task-generator 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 适用于敏捷开发与计划驱动混合模式。

SKILL.md

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: specs/{task_name}/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 step{NN}/ folder (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:

---
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]

Examples

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.

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.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Claude Code

30.25%
按下载量换算89

Gemini CLI

21.82%
按下载量换算64

Antigravity

18.14%
按下载量换算53

windsurf

12.32%
按下载量换算36

Codex

6.82%
按下载量换算20

OpenCode

3.52%
按下载量换算10

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。

来源信息

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