Best for
- After planning phase completes
- Ready to implement tasks
- Need systematic execution with tracking
athola/claude-night-market/plugins/attune/skills/project-execution/SKILL.md
Executes implementation plans with progress tracking, checkpoint validation, and quality gates. Use after planning is complete and tasks are ready to implement.
Decision brief
Executes implementation plans with progress tracking, checkpoint validation, and quality gates. Use after planning is complete and tasks are ready to implement.
Compatibility matrix
| Platform | Status | Evidence | What to check |
|---|---|---|---|
| Codex | Not declared | No explicit evidence | Portability before use |
| Claude Code | Not declared | No explicit evidence | Portability before use |
| Cursor | Not declared | No explicit evidence | Portability before use |
| Gemini CLI | Not declared | No explicit evidence | Portability before use |
Installation
The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.
npx skills add https://github.com/athola/claude-night-market --skill "plugins/attune/skills/project-execution"Inspect the Agent Skill "project-execution" from https://github.com/athola/claude-night-market/blob/6720bb5cdeadeea6de6e4786a449126b3d417536/plugins/attune/skills/project-execution/SKILL.md at commit 6720bb5cdeadeea6de6e4786a449126b3d417536. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.
Workflow
Actions: 1. Load implementation plan 2. Validate project initialized 3. Check dependencies installed 4. Review task dependency graph 5. Identify starting tasks (no dependencies)
Actions: 1. Verify all tasks complete 2. Run full test suite 3. Check code quality metrics 4. Generate completion report 5. Prepare for deployment/release 6. Record lessons learned (see below)
This is the final phase of the attune workflow. No auto-continuation occurs after execution completes. The workflow terminates here. Unlike brainstorming, specification, and planning phases, execution does NOT auto-invoke any subsequent phase.
Review the “TDD Workflow” section in the pinned source before continuing.
After planning phase completes
Permission review
The documentation asks the agent to run terminal commands or scripts.
make lint # Linting passesThe documentation asks the agent to run terminal commands or scripts.
make typecheck # Type checking passesEvidence record
| Signal | Value | Evidence type | Meaning |
|---|---|---|---|
| Quality score | 93/100 | Computed | Documentation, specificity, maintenance, and trust rules |
| Repository stars | 331 | Source | Repository attention, not individual Skill quality |
| Compatibility | 0 platforms | Source | Declared in the catalog source record |
| Usage guide | automated source guide | Editorial | Generated or reviewed according to the visible evidence level |
Pinned source
Skill(attune:project-planning) first)With superpowers:
Skill(superpowers:executing-plans) for systematic executionSkill(superpowers:systematic-debugging) for issue resolutionSkill(superpowers:verification-before-completion) for validationSkill(superpowers:test-driven-development) for TDD workflowWith imbue:
Skill(imbue:graduated-implementation) at the ramp gate so
each increment's ambition is earned by demonstrated understanding
of the prior one, not ramped on completion aloneWithout superpowers:
Actions:
Validation:
For each task in dependency order:
1. PRE-TASK
- Verify dependencies complete
- Review acceptance criteria
- Create feature branch (optional)
- Set up task context
2. IMPLEMENT (TDD Cycle)
- Write failing test (RED)
- Implement minimal code (GREEN)
- Refactor for quality (REFACTOR)
- Repeat until all criteria met
3. VALIDATE
- All tests passing?
- All acceptance criteria met?
- Code quality checks pass?
- Documentation updated?
4. RAMP GATE (before the next, more ambitious task)
- Invoke Skill(imbue:graduated-implementation)
- Demonstrate understanding of THIS increment, sized to stakes:
low-stakes on the evidence gate (green tests plus a recorded
tradeoff), high-stakes on the human explaining the diff unaided
- On a clean demonstration, record it in the ramp ledger and
mark the rung widened; below the band, hold and split the next
task smaller instead of ramping
5. CHECKPOINT
- Mark task complete IMMEDIATELY (do NOT batch)
- Update execution state
- Report progress
- Identify blockers
Task Completion Discipline: Always call TaskUpdate(taskId: "X", status: "completed") right after finishing each task. Never defer completions to end of session.
Verification: Run pytest -v to verify tests pass.
Actions:
Implementation is where the honest lessons appear: the approach that had to be
reworked, the blocker that cost a day, the assumption from planning that did
not hold. Capture these in docs/lessons-learned.md now, blamelessly, instead
of letting them vanish into "done." Draft and confirm one entry per
substantive lesson:
Skill(leyline:decision-journal) and follow
it to append a lesson entry: what_happened, what_didnt_work,
root_cause, and a concrete action. Set phase to execute. Show the
draft; append on confirmation (status starts open).docs/lessons-learned.md by hand using
the in-file ENTRY TEMPLATE; assign the next LL-NNN id.Trigger this whenever execution involved rework, a failed approach, or a blocker that exhausted the two-challenge / 3-attempt limit. A clean run with no surprises needs no entry.
This is the final phase of the attune workflow. No auto-continuation occurs after execution completes. The workflow terminates here. Unlike brainstorming, specification, and planning phases, execution does NOT auto-invoke any subsequent phase.
Before implementing a task, delegate it.
Skill(conjure:delegation-core) is on by default, so the decision to
make is whether a Keep Local clause holds, not whether to bother.
Keep the task local when it is design or trade-off work, when its context carries a secret, when it needs turn-by-turn iteration, or when its output cannot be validated afterward. Otherwise hand it to the delegator and validate what comes back through the same TDD workflow below. The tests are the validation: a delegated implementation that fails the RED test is rejected exactly like a local one.
If the result carries a fallback_reason, no external model ran.
Report which providers were tried, then implement the task here.
An exhausted chain is not a blocked task and does not belong in
docs/lessons-learned.md.
RED Phase:
# Write test that fails
def test_user_authentication():
user = authenticate("[email protected]", "password")
assert user.is_authenticated
# Run test → FAILS (feature not implemented)
Verification: Run pytest -v to verify tests pass.
GREEN Phase:
# Implement minimal code to pass
def authenticate(email, password):
# Simplest implementation
user = User.find_by_email(email)
if user and user.check_password(password):
user.is_authenticated = True
return user
return None
# Run test → PASSES
Verification: Run pytest -v to verify tests pass.
REFACTOR Phase:
# Improve code quality
def authenticate(email: str, password: str) -> Optional[User]:
"""Authenticate user with email and password."""
user = User.find_by_email(email)
if user is None:
return None
if not user.check_password(password):
return None
user.mark_authenticated()
return user
# Run test → STILL PASSES
Verification: Run pytest -v to verify tests pass.
Quality Gates:
- [ ] All acceptance criteria met
- [ ] All tests passing (unit + integration)
- [ ] Code linted (no warnings)
- [ ] Type checking passes (if applicable)
- [ ] Documentation updated
- [ ] No regression in other components
Verification: Run pytest -v to verify tests pass.
Automated Checks:
# Run quality gates
make lint # Linting passes
make typecheck # Type checking passes
make test # All tests pass
uv run pytest --cov # Coverage threshold met
Verification: Run pytest -v to verify tests pass.
Save to .attune/execution-state.json:
{
"plan_file": "docs/implementation-plan.md",
"started_at": "2026-01-02T10:00:00Z",
"last_checkpoint": "2026-01-02T14:30:22Z",
"current_sprint": "Sprint 1",
"current_phase": "Phase 1",
"tasks": {
"TASK-001": {
"status": "complete",
"started_at": "2026-01-02T10:05:00Z",
"completed_at": "2026-01-02T10:50:00Z",
"duration_minutes": 45,
"acceptance_criteria_met": true,
"tests_passing": true
},
"TASK-002": {
"status": "in_progress",
"started_at": "2026-01-02T14:00:00Z",
"progress_percent": 60,
"blocker": null
}
},
"metrics": {
"tasks_complete": 15,
"tasks_total": 40,
"completion_percent": 37.5,
"velocity_tasks_per_day": 3.2,
"estimated_completion_date": "2026-02-15"
},
"blockers": []
}
Verification: Run pytest -v to verify tests pass.
Daily Standup:
# Daily Standup - [Date]
## Yesterday
- ✅ [Task] ([duration])
- ✅ [Task] ([duration])
## Today
- 🔄 [Task] ([progress]%)
- 📋 [Task] (planned)
## Blockers
- [Blocker] or None
## Metrics
- Sprint progress: [X/Y] tasks ([%]%)
- [Status message]
Verification: Run the command with --help flag to verify availability.
Sprint Report:
# Sprint [N] Progress Report
**Dates**: [Start] - [End]
**Goal**: [Sprint objective]
## Completed ([X] tasks)
- [Task list]
## In Progress ([Y] tasks)
- [Task] ([progress]%)
## Blocked ([Z] tasks)
- [Task]: [Blocker description]
## Burndown
- Day 1: [N] tasks remaining
- Day 5: [M] tasks remaining ([status])
- Estimated completion: [Date] ([delta])
## Risks
- [Risk] or None identified
Verification: Run the command with --help flag to verify availability.
Common Blockers:
When blocked, apply debugging framework:
When to escalate:
Escalation format:
## Blocker: [TASK-XXX] - [Issue]
**Symptom**: [What's happening]
**Impact**: [Which tasks/timeline affected]
**Attempted Solutions**:
1. [Solution 1] - [Result]
2. [Solution 2] - [Result]
**Recommendation**: [Proposed path forward]
**Decision Needed**: [What needs to be decided]
Verification: Run the command with --help flag to verify availability.
Task is complete when:
Test Pyramid:
**Verification:** Run `pytest -v` to verify tests pass.
/\
/E2E\ Few, slow, expensive
/------\
/ INT \ Some, moderate speed
/----------\
/ UNIT \ Many, fast, cheap
Verification: Run the command with --help flag to verify availability.
Per Task:
Track daily:
Formulas:
**Verification:** Run `pytest -v` to verify tests pass.
Velocity = Tasks completed / Days elapsed
Estimated completion = Tasks remaining / Velocity
On track? = Estimated completion <= Sprint end date
Verification: Run the command with --help flag to verify availability.
If ahead of schedule:
If behind schedule:
docs/lessons-learned.md as an open entry (a clean run needs none).Skill(superpowers:executing-plans) - Execution framework (if available)Skill(superpowers:systematic-debugging) - Debugging (if available)Skill(superpowers:test-driven-development) - TDD (if available)Skill(superpowers:verification-before-completion) - Validation (if available)Skill(conjure:delegation-core) - Default-on delegation of task executionSkill(attune:mission-orchestrator) - Full lifecycle orchestrationAgent(attune:project-implementer) - Task execution agent/attune:execute - Invoke this skill/attune:execute --task [ID] - Execute specific task/attune:execute --resume - Resume from checkpointAt mission completion, produce a Mission Report using the
template from references/mission-report.md. The report documents:
See references/mission-report.md for the full template and
example reports for successful, partial, and failed missions.
See /attune:execute command documentation for complete examples.
Frequently asked questions
Executes implementation plans with progress tracking, checkpoint validation, and quality gates. Use after planning is complete and tasks are ready to implement.
The source record exposes this install command: npx skills add https://github.com/athola/claude-night-market --skill "plugins/attune/skills/project-execution". Inspect the command and pinned source before running it.
Static rules flagged exec-script in the source; the page lists the matching lines and excerpts.
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