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generate-tasks生成任务

Agent Skill

generate-tasks 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。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

272

周安装

11

GitHub Stars

8

下载量

85
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

2

许可证

unknown

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:generate-tasks(生成任务)
来源仓库:https://github.com/ar4mirez/samuel
仓库路径:skills/generate-tasks
安装命令:
npx skills add https://github.com/ar4mirez/samuel --skill generate-tasks
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。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/ar4mirez/samuel --skill generate-tasks

简介

用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息。

  • 适合在 Codex、Claude、Cursor、Gemini CLI 中围绕仓库状态或代码变更时使用。
  • 通过 GitHub 安装,使用 npx skills add 命令添加技能。
  • 需确认权限范围和维护状态,注意是否触发联网或文件读写。
  • generate-tasks 属于前端设计类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Skill: Generate Task List from PRD

Overview

Guide AI in creating detailed, step-by-step task list in Markdown format based on existing PRD. The task list should guide a developer through implementation with built-in quality checkpoints.

Use When: PRD created, ready to plan implementation 4D Phase: Develop (planning implementation steps)

Prerequisites

Before using this skill:

  • PRD exists in .claude/tasks/NNNN-prd-feature-name.md
  • PRD reviewed and approved by user
  • CLAUDE.md exists (or will be created during this process)
  • Current codebase reviewed for context

Process Overview

Two-Phase Approach

Phase 1: Generate parent tasks → Present to user → Wait for "Go" Phase 2: Generate detailed sub-tasks → Save file → Inform user

This ensures high-level plan approved before diving into details.

Phase 1: Analysis & High-Level Planning

Step 1: Receive PRD Reference

User points AI to specific PRD file.

Example:

"Generate tasks for @.claude/tasks/0001-prd-user-authentication.md using @.claude/skills/generate-tasks/SKILL.md"

Step 2: Read PRD

AI reads and analyzes:

  • Functional requirements
  • User stories
  • Technical considerations
  • Guardrails affected
  • Success metrics

Step 3: Assess Current State

CRITICAL: Review existing codebase before planning.

AI must:

  1. Check CLAUDE.md for:

- Tech stack and framework choices - Existing architecture patterns - Testing framework and conventions - Deployment configuration

  1. Scan codebase for:

- Existing directory structure - Similar features (auth, API routes, etc.) - Naming conventions - Test file patterns - Component organization

  1. Identify reusable components:

- Existing utilities that can be leveraged - UI components from design system - Database connection patterns - Error handling patterns - Validation utilities

  1. Check guardrails compliance:

- Current file lengths (don't add to files approaching limits) - Existing test coverage patterns - Security patterns in use - Performance considerations

Output: Brief summary for user review before generating tasks.

Example:

## Current State Assessment

**Existing Infrastructure:**
- Express.js backend with TypeScript
- Prisma ORM with PostgreSQL
- Jest for testing (78% coverage currently)
- React frontend with Tailwind CSS

**Reusable Components:**
- `lib/validation.ts` - Input validation utilities (use Zod)
- `components/Form.tsx` - Form component (reuse for auth forms)
- `lib/errors.ts` - Centralized error handling (extend for auth errors)

**Patterns to Follow:**
- API routes in `src/api/<feature>/` structure
- Tests alongside code (`*.test.ts`)
- Repository pattern for data access
- Environment variables via `.env` with fallbacks

**Guardrails Note:**
- `src/api/user/user.controller.ts` is 285 lines (near 300 limit - don't modify)
- Create new auth module instead of extending user module

Step 4: Generate Parent Tasks

Based on PRD and current state, create high-level tasks.

Guidelines:

  • Typically 4-7 parent tasks
  • Each parent = logical phase of implementation
  • Order by dependency (database → backend → frontend → tests)
  • Include setup, implementation, testing, documentation

Save to: .claude/tasks/tasks-NNNN-prd-feature-name.md

Present to user in this format:

## High-Level Tasks

- [ ] 1.0 Database Schema & Migrations
- [ ] 2.0 Backend Authentication Service
- [ ] 3.0 API Routes & Middleware
- [ ] 4.0 Frontend Auth Components
- [ ] 5.0 OAuth Integration
- [ ] 6.0 Testing & Validation
- [ ] 7.0 Documentation & Deployment

**Relevant Files** (identified):
- `src/db/schemas/user.schema.ts` - Create
- `src/auth/auth.service.ts` - Create
- `src/api/auth/auth.controller.ts` - Create
... (full list in task file)

Then inform user:

"High-level tasks generated. Review the task structure above.
Ready to generate detailed sub-tasks? Respond with 'Go' to proceed."

Step 5: Wait for User Confirmation

PAUSE - Do not proceed until user responds with "Go" or equivalent.

This checkpoint ensures high-level plan aligns with expectations before diving into details.


Phase 2: Detailed Task Breakdown

Step 6: Generate Sub-Tasks

Once user confirms "Go", break down each parent task into actionable sub-tasks.

Sub-task Guidelines:

  1. Granularity: Each sub-task = 30-60 min of work (3,000-6,000 tokens)
  2. Atomicity: Complete in one session, one commit
  3. Testability: Each sub-task includes verification step
  4. Dependency: Clear which sub-tasks depend on others
  5. Guardrails: Each task validates against relevant guardrails

Sub-task Naming Convention:

  • Use present tense verbs: "Create", "Implement", "Add", "Update", "Test"
  • Be specific: "Create user schema" not "Setup database"
  • Include success criterion: "Create user schema (with email, password_hash, created_at fields)"

Example Parent → Sub-tasks:

- [ ] 1.0 Database Schema & Migrations
  - [ ] 1.1 Create user schema with Prisma (email, password_hash, oauth_provider, created_at, updated_at)
  - [ ] 1.2 Create session schema with Prisma (user_id FK, token, expires_at, created_at)
  - [ ] 1.3 Generate and run Prisma migration for user and session tables
  - [ ] 1.4 Verify schema in PostgreSQL (check indexes, constraints)
  - [ ] 1.5 Update .env.example with DATABASE_URL placeholder

Step 7: Add Guardrail Validation Per Task

For each sub-task, identify which guardrails must be validated.

Format: Add guardrail checklist as comment under relevant tasks.

Example:

- [ ] 2.3 Implement password hashing service (bcrypt, cost factor 12)
  <!-- Guardrails:
    ✓ All environment variables have secure defaults (BCRYPT_ROUNDS=12)
    ✓ All exported functions have type signatures and JSDoc
    ✓ Function ≤50 lines (hash, verify, validate strength as separate functions)
    ✓ Edge cases tested (null, empty, too short, invalid chars)
  -->

Step 8: Add Complexity Estimates

For each sub-task, estimate complexity in tokens (not time).

Complexity Levels:

  • Simple: <2,000 tokens (single function, straightforward logic)
  • Medium: 2,000-5,000 tokens (multiple functions, some complexity)
  • Complex: 5,000-10,000 tokens (multiple files, integration, edge cases)

Example:

- [ ] 2.3 Implement password hashing service [~3,000 tokens - Medium]

Step 9: Identify Relevant Files

List all files that will be created or modified, including tests.

Format: See references/process.md for detailed file listing format.

Step 10: Add Implementation Notes

Provide guidance for each task section.

Include:

  • Testing requirements specific to this feature
  • Performance considerations
  • Security reminders
  • Integration points
  • Common pitfalls to avoid

Example:

## Implementation Notes

### Testing Requirements
- All auth logic must have >95% coverage (business-critical)
- Test files alongside code (e.g., `auth.service.ts` + `auth.service.test.ts`)
- Use `npm test src/auth` to run auth module tests only
- Integration tests must test actual JWT validation, not mocks

### Security Checklist (verify before each commit)
- [ ] All passwords hashed (never store plain text)
- [ ] All JWT secrets from environment variables
- [ ] All inputs validated with Zod schemas
- [ ] All SQL queries parameterized (use Prisma)
- [ ] Rate limiting on login/register endpoints
- [ ] Authentication events logged

### Performance Targets
- Login/register: <200ms (p95)
- JWT validation: <50ms (p95)
- Password hashing: 100-300ms (bcrypt cost 12)

### Common Pitfalls
- ❌ Don't validate JWT in database query (use middleware)
- ❌ Don't store tokens in localStorage (use httpOnly cookies)
- ❌ Don't return sensitive data in error messages
- ❌ Don't skip rate limiting (prevents brute force)

Step 11: Generate Final Output

Combine all sections into final task list structure.

See references/process.md for complete output format template.


Output Location

File: .claude/tasks/tasks-NNNN-prd-feature-name.md Format: Markdown Naming: Match PRD filename (e.g., PRD is 0001-prd-user-auth.md → tasks are tasks-0001-prd-user-auth.md)


Implementation Workflow

During Implementation

User will say: "Start on task 1.1" or "Continue with next task"

AI should:

  1. Implement the specific sub-task
  2. Write tests alongside code
  3. Validate against guardrails in task comment
  4. Run tests
  5. Verify success criteria
  6. Commit with message: feat(auth): task 1.1 - create user schema
  7. Mark task complete in task list file
  8. Ask: "Task 1.1 complete. Review changes? Or continue with 1.2?"

Guardrails Integration

For each sub-task, identify which of CLAUDE.md's 30+ guardrails apply.

Common guardrails per task type:

Database Schema Tasks

  • ✓ All environment variables have secure defaults
  • ✓ Parameterized queries (Prisma enforces this)

Service/Logic Tasks

  • ✓ No function exceeds 50 lines
  • ✓ Cyclomatic complexity ≤10 per function
  • ✓ All exported functions have type signatures and JSDoc
  • ✓ All user inputs validated before processing

API/Route Tasks

  • ✓ All API boundaries have input validation (Zod schemas)
  • ✓ All async operations have timeout/cancellation
  • ✓ API responses <200ms for simple queries

Test Tasks

  • ✓ Coverage targets: >95% for auth (business-critical)
  • ✓ All public APIs have unit tests
  • ✓ Edge cases tested (null, empty, boundary values)
  • ✓ No test interdependencies

Security Tasks (Auth-related)

  • ✓ All user inputs validated before processing
  • ✓ All database queries parameterized
  • ✓ All environment variables have secure defaults
  • ✓ Dependencies checked for vulnerabilities

Final Instructions

For AI Assistant:

Phase 1 (High-Level):

  1. ✅ Read PRD thoroughly
  2. ✅ Assess current codebase (scan for existing patterns)
  3. ✅ Generate 4-7 parent tasks
  4. ✅ Identify all relevant files
  5. ✅ Present to user
  6. WAIT for "Go" before Phase 2

Phase 2 (Detailed):

  1. ✅ Break each parent into 3-8 sub-tasks
  2. ✅ Add guardrail validation per task
  3. ✅ Add complexity estimates
  4. ✅ Add implementation notes
  5. ✅ Save task list file
  6. ✅ Inform user: "Task list ready at [path]. Ready to start task 1.1?"

During Implementation:

  1. ✅ Implement one sub-task at a time
  2. ✅ Validate guardrails for that specific task
  3. ✅ Write tests alongside code
  4. ✅ Commit after each task (atomic commits)
  5. ✅ Update task list (mark completed)
  6. ✅ Ask user to review before continuing

Target Audience

Primary: Junior developer with AI assistance Assumption: Developer knows fundamentals but needs clear guidance on:

  • Where to create files
  • What patterns to follow
  • Which guardrails to validate
  • How to test properly

References

See references/process.md for:

  • Complete output format template
  • Detailed file listing examples
  • Extended implementation notes
  • Full task breakdown examples

Remember: Good task breakdown = clear roadmap. Each sub-task should be:

  • Atomic: Complete in one session
  • Testable: Has clear success criterion
  • Guarded: Validates specific guardrails
  • Estimated: Complexity known upfront
  • Dependent: Dependencies clear (order matters)

Autonomous Execution (Optional)

If the project uses autonomous AI coding loops (Ralph Wiggum methodology), the generated task list can be converted to machine-readable format for unattended execution.

After generating the markdown task list:

samuel auto init --prd .claude/tasks/NNNN-prd-feature.md

This converts the PRD and task list into .claude/auto/prd.json and generates the loop orchestration files. See .claude/skills/auto/SKILL.md for the full autonomous workflow.

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

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

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

Codex

35.03%
按下载量换算30

Claude

31.2%
按下载量换算27

Cursor

19.66%
按下载量换算17

Gemini CLI

8.73%
按下载量换算7

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

敏感数据

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安装前确认

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