General

feature-pipeline - Claude MCP Skill

Execute implementation tasks from design documents using markdown checkboxes. Use when (1) implementing features from feature-analyzer output, (2) resuming interrupted work, (3) batch executing tasks. Triggers on 'start implementation', 'run tasks', 'resume'.

SEO Guide: Enhance your AI agent with the feature-pipeline tool. This Model Context Protocol (MCP) server allows Claude Desktop and other LLMs to execute implementation tasks from design documents using markdown checkboxes. use when (1) implement... Download and configure this skill to unlock new capabilities for your AI workflow.

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Documentation

SKILL.md
# Feature Pipeline

Execute implementation tasks directly from design documents. Tasks are managed as markdown checkboxes - no separate session files needed.

## Quick Reference

```bash
# Get next task
python3 scripts/task_manager.py next --file <design.md>

# Mark task completed
python3 scripts/task_manager.py done --file <design.md> --task "Task Title"

# Mark task failed
python3 scripts/task_manager.py fail --file <design.md> --task "Task Title" --reason "..."

# Show status
python3 scripts/task_manager.py status --file <design.md>
```

## Task Format

Tasks are written as markdown checkboxes in the design document:

```markdown
## Implementation Tasks

- [ ] **Create User model** `priority:1` `phase:model`
  - files: src/models/user.py, tests/models/test_user.py
  - [ ] User model has email and password_hash fields
  - [ ] Email validation implemented
  - [ ] Password hashing uses bcrypt

- [ ] **Implement JWT utils** `priority:2` `phase:model`
  - files: src/utils/jwt.py
  - [ ] generate_token() creates valid JWT
  - [ ] verify_token() validates JWT

- [ ] **Create auth API** `priority:3` `phase:api` `deps:Create User model,Implement JWT utils`
  - files: src/api/auth.py
  - [ ] POST /register endpoint
  - [ ] POST /login endpoint
```

See [references/task-format.md](references/task-format.md) for full format specification.

## Execution Loop

```
LOOP until no tasks remain:
  1. GET next task (task_manager.py next)
  2. READ task details (files, criteria)
  3. IMPLEMENT the task
  4. VERIFY acceptance criteria
  5. UPDATE status (task_manager.py done/fail)
  6. CONTINUE
```

### Unattended Mode Rules

- **NO stopping** for questions
- **NO asking** for clarification
- Make autonomous decisions based on codebase patterns
- If blocked, mark as failed and continue

## Status Updates

Completed task:
```markdown
- [x] **Create User model** `priority:1` `phase:model` ✅
  - files: src/models/user.py
  - [x] User model has email field
  - [x] Password hashing implemented
```

Failed task:
```markdown
- [x] **Create User model** `priority:1` `phase:model` ❌
  - files: src/models/user.py
  - [ ] User model has email field
  - reason: Missing database configuration
```

## Resume / Recovery

To resume interrupted work, simply run again with the same design file:

```
/feature-pipeline docs/designs/xxx.md
```

The task manager will find the first uncompleted task and continue from there.

## Integration

This skill is typically triggered after `/feature-analyzer` completes:

```
User: /feature-analyzer implement user auth

Claude: [designs feature, generates task list]
        Design saved to docs/designs/2026-01-02-user-auth.md
        Ready to start implementation?

User: Yes / 开始实现

Claude: [executes tasks via feature-pipeline]
```

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Information

Repository
notedit/happy-coding-agent
Author
notedit
Last Sync
3/3/2026
Repo Updated
3/2/2026
Created
1/25/2026

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