ReddRadar
Agent skill
task-execution-engine
Execute implementation tasks from design documents using markdown checkboxes. Use when (1) implementing features from feature-design-assistant output, (2) resuming interrupted work, (3) batch executing tasks. Triggers on 'start implementation', 'run tasks', 'resume'.
Install this agent skill to your Project
npx add-skill https://github.com/davila7/claude-code-templates/tree/main/cli-tool/components/skills/development/task-execution-engine
SKILL.md
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 task-execution-engine]
Recommended Agent Skills
Expand your agent's capabilities with these related and highly-rated skills.
davila7/claude-code-templates
verl-rl-training
Provides guidance for training LLMs with reinforcement learning using verl (Volcano Engine RL). Use when implementing RLHF, GRPO, PPO, or other RL algorithms for LLM post-training at scale with flexible infrastructure backends.
davila7/claude-code-templates
openrlhf-training
High-performance RLHF framework with Ray+vLLM acceleration. Use for PPO, GRPO, RLOO, DPO training of large models (7B-70B+). Built on Ray, vLLM, ZeRO-3. 2× faster than DeepSpeedChat with distributed architecture and GPU resource sharing.
davila7/claude-code-templates
gguf-quantization
GGUF format and llama.cpp quantization for efficient CPU/GPU inference. Use when deploying models on consumer hardware, Apple Silicon, or when needing flexible quantization from 2-8 bit without GPU requirements.
davila7/claude-code-templates
Claude Code Guide
Master guide for using Claude Code effectively. Includes configuration templates, prompting strategies "Thinking" keywords, debugging techniques, and best practices for interacting with the agent.
davila7/claude-code-templates
qdrant-vector-search
High-performance vector similarity search engine for RAG and semantic search. Use when building production RAG systems requiring fast nearest neighbor search, hybrid search with filtering, or scalable vector storage with Rust-powered performance.
davila7/claude-code-templates
behavioral-modes
AI operational modes (brainstorm, implement, debug, review, teach, ship, orchestrate). Use to adapt behavior based on task type.
Didn't find tool you were looking for?