feature-pipeline
Turns design documentation tasks into actionable, tracked code implementation steps.
Install
mkdir -p .claude/skills/feature-pipeline && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/5110" && unzip -o skill.zip -d .claude/skills/feature-pipeline && rm skill.zipInstalls to .claude/skills/feature-pipeline
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
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'.Key capabilities
- →Parse markdown task lists
- →Execute tasks sequentially
- →Track task completion status
- →Handle task failure reporting
- →Resume interrupted workflows
How it works
It uses a script to parse markdown checkboxes in a design document, allowing the agent to track progress and execute tasks autonomously.
Inputs & outputs
When to use feature-pipeline
- →Implementing features from design docs
- →Resuming interrupted coding sessions
- →Batch executing complex feature tasks
About this skill
Feature Pipeline
Execute implementation tasks directly from design documents. Tasks are managed as markdown checkboxes - no separate session files needed.
Quick Reference
# 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:
## 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 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:
- [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:
- [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]
When not to use it
- →For non-markdown based task lists
Limitations
- →Requires tasks to be formatted as markdown checkboxes
- →Autonomous decisions rely on existing codebase patterns
How it compares
It maintains state directly within the design document using markdown, eliminating the need for external session tracking files.
Compared to similar skills
feature-pipeline side by side with the closest alternatives in the catalog.
Try saying
Example prompts that trigger this skill in your AI assistant.
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