Use when executing implementation plans with independent tasks. Dispatches fresh delegate_task per task with two-stage review (spec compliance then code quality).
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Use when executing implementation plans with independent tasks. Dispatches fresh delegate_task per task with two-stage review (spec compliance then code quality).
Execute implementation plans by dispatching fresh subagents per task with systematic two-stage review.
Core principle: Fresh subagent per task + two-stage review (spec then quality) = high quality, fast iteration.
When to Use
Use this skill when:
You have an implementation plan (from writing-plans skill or user requirements)
Tasks are mostly independent
Quality and spec compliance are important
You want automated review between tasks
vs. manual execution:
Fresh context per task (no confusion from accumulated state)
Automated review process catches issues early
Consistent quality checks across all tasks
Subagents can ask questions before starting work
The Process
1. Read and Parse Plan
Read the plan file. Extract ALL tasks with their full text and context upfront. Create a todo list:
# Read the plan
read_file("docs/plans/feature-plan.md")
# Create todo list with all tasks
todo([
{"id": "task-1", "content": "Create User model with email field", "status": "pending"},
{"id": "task-2", "content": "Add password hashing utility", "status": "pending"},
{"id": "task-3", "content": "Create login endpoint", "status": "pending"},
])
Key: Read the plan ONCE. Extract everything. Don't make subagents read the plan file — provide the full task text directly in context.
2. Per-Task Workflow
For EACH task in the plan:
Step 1: Dispatch Implementer Subagent
Use delegate_task with complete context:
delegate_task(
goal="Implement Task 1: Create User model with email and password_hash fields",
context="""
TASK FROM PLAN:
- Create: src/models/user.py
- Add User class with email (str) and password_hash (str) fields
- Use bcrypt for password hashing
- Include __repr__ for debugging
FOLLOW TDD:
1. Write failing test in tests/models/test_user.py
2. Run: pytest tests/models/test_user.py -v (verify FAIL)
3. Write minimal implementation
4. Run: pytest tests/models/test_user.py -v (verify PASS)
5. Run: pytest tests/ -q (verify no regressions)
6. Commit: git add -A && git commit -m "feat: add User model with password hashing"
PROJECT CONTEXT:
- Python 3.11, Flask app in src/app.py
- Existing models in src/models/
- Tests use pytest, run from project root
- bcrypt already in requirements.txt
""",
toolsets=['terminal', 'file']
)
Step 2: Dispatch Spec Compliance Reviewer
After the implementer completes, verify against the original spec:
delegate_task(
goal="Review if implementation matches the spec from the plan",
context="""
ORIGINAL TASK SPEC:
- Create src/models/user.py with User class
- Fields: email (str), password_hash (str)
- Use bcrypt for password hashing
- Include __repr__
CHECK:
- [ ] All requirements from spec implemented?
- [ ] File paths match spec?
- [ ] Function signatures match spec?
- [ ] Behavior matches expected?
- [ ] Nothing extra added (no scope creep)?
OUTPUT: PASS or list of specific spec gaps to fix.
""",
toolsets=['file']
)
If spec issues found: Fix gaps, then re-run spec review. Continue only when spec-compliant.
Step 3: Dispatch Code Quality Reviewer
After spec compliance passes:
delegate_task(
goal="Review code quality for Task 1 implementation",
context="""
FILES TO REVIEW:
- src/models/user.py
- tests/models/test_user.py
CHECK:
- [ ] Follows project conventions and style?
- [ ] Proper error handling?
- [ ] Clear variable/function names?
- [ ] Adequate test coverage?
- [ ] No obvious bugs or missed edge cases?
- [ ] No security issues?
OUTPUT FORMAT:
- Critical Issues: [must fix before proceeding]
- Important Issues: [should fix]
- Minor Issues: [optional]
- Verdict: APPROVED or REQUEST_CHANGES
""",
toolsets=['file']
)
If quality issues found: Fix issues, re-review. Continue only when approved.
Step 4: Mark Complete
todo([{"id": "task-1", "content": "Create User model with email field", "status": "completed"}], merge=True)
3. Final Review
After ALL tasks are complete, dispatch a final integration reviewer:
delegate_task(
goal="Review the entire implementation for consistency and integration issues",
context="""
All tasks from the plan are complete. Review the full implementation:
- Do all components work together?
- Any inconsistencies between tasks?
- All tests passing?
- Ready for merge?
""",
toolsets=['terminal', 'file']
)
4. Verify and Commit
# Run full test suite
pytest tests/ -q
# Review all changes
git diff --stat# Final commit if needed
git add -A && git commit -m "feat: complete [feature name] implementation"
Task Granularity
Each task = 2-5 minutes of focused work.
Too big:
"Implement user authentication system"
Right size:
"Create User model with email and password fields"
"Add password hashing function"
"Create login endpoint"
"Add JWT token generation"
"Create registration endpoint"
Red Flags — Never Do These
Start implementation without a plan
Skip reviews (spec compliance OR code quality)
Proceed with unfixed critical/important issues
Dispatch multiple implementation subagents for tasks that touch the same files
Make subagent read the plan file (provide full text in context instead)
Skip scene-setting context (subagent needs to understand where the task fits)
Ignore subagent questions (answer before letting them proceed)
