跳到主要内容
知仓学习社ZHICANG

project-execution

Executes implementation plans with progress tracking, checkpoint validation, and quality gates. Use after planning is complete and tasks are ready t…

不碰外部(只输出文字)无严重或高危命中athola/claude-night-market

它会碰到什么

扫了多少2 个文本文件,26 KB
它会碰到什么不碰外部(只输出文字)
命中总数0 处
命中统计严重 0 · 高 0 · 中 0 · 低 0

这一栏是扫描器报的事实,不是结论。命中多不等于有毒(安全工具、规则库、示例脚本本来就会包含危险写法),命中少也不等于干净。它和你手上的凭据、文件、网络有什么关系,需要你自己看。

技能内容

When To Use

  • After planning phase completes
  • Ready to implement tasks
  • Need systematic execution with tracking
  • Want checkpoint-based validation
  • Executing task lists with dependencies
  • Monitoring progress and velocity

When NOT To Use

  • No implementation plan exists (use Skill(attune:project-planning) first)
  • Still planning or designing (complete planning phase before execution)
  • Single isolated task (execute directly without framework overhead)
  • Exploratory coding or prototyping (use focused development instead)

Integration

With superpowers:

  • Uses Skill(superpowers:executing-plans) for systematic execution
  • Uses Skill(superpowers:systematic-debugging) for issue resolution
  • Uses Skill(superpowers:verification-before-completion) for validation
  • Uses Skill(superpowers:test-driven-development) for TDD workflow

With imbue:

  • Uses 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 alone

Without superpowers:

  • Standalone execution framework
  • Built-in checkpoint validation
  • Progress tracking patterns

Execution Framework

Pre-Execution Phase

Actions:

  1. Load implementation plan
  2. Validate project initialized
  3. Check dependencies installed
  4. Review task dependency graph
  5. Identify starting tasks (no dependencies)

Validation:

  • ✅ Plan file exists and is valid
  • ✅ Project structure initialized
  • ✅ Git repository configured
  • ✅ Development environment ready

Task Execution Loop

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.

Post-Execution Phase

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)

Record Lessons Learned (decision journal)

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:

  • If leyline is installed, invoke 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).

  • Fallback (leyline absent): append to 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.

Terminal Phase Notice

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.

Task Execution Pattern

Delegation Check (First, Per Task)

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.

TDD Workflow

RED Phase:

# Write test that fails
def test_user_authentication():
    user = authenticate("user@example.com", "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.

Checkpoint Validation

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.

Progress Tracking

Execution State

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.

Progress Reports

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.

Blocker Management

Blocker Detection

Common Blockers:

  • Failing tests that can't be fixed quickly
  • Missing dependencies or APIs
  • Technical unknowns requiring research
  • Resource unavailability
  • Scope ambiguity

Systematic Debugging

When blocked, apply debugging framework:

  1. Reproduce: Create minimal reproduction case
  2. Hypothesize: Generate possible causes
  3. Test: Validate hypotheses one by one
  4. Resolve: Implement fix or workaround
  5. Document: Record solution for future

Escalation

When to escalate:

  • Blocker persists > 2 hours
  • Requires architecture change
  • Impacts critical path
  • Needs stakeholder decision

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.

Quality Assurance

Definition of Done

Task is complete when:

  • ✅ All acceptance criteria met
  • ✅ All tests written and passing
  • ✅ Code reviewed (self or peer)
  • ✅ Linting passes with no warnings
  • ✅ Type checking passes (if applicable)
  • ✅ Documentation updated
  • ✅ No known regressions
  • ✅ Deployed to staging (if applicable)

Testing Strategy

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:

  • Unit tests: Test individual functions/classes
  • Integration tests: Test component interactions
  • E2E tests: Test complete user flows (for user-facing features)

Velocity Tracking

Burndown Metrics

Track daily:

  • Tasks remaining
  • Story points remaining
  • Days left in sprint
  • Velocity (tasks or points per day)

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.

Velocity Adjustments

If ahead of schedule:

  • Pull in stretch tasks
  • Add technical debt reduction
  • Improve test coverage
  • Enhance documentation

If behind schedule:

  • Identify causes (blockers, underestimation)
  • Reduce scope (drop low-priority tasks)
  • Increase focus (reduce distractions)
  • Request help or extend timeline

Exit Criteria

  • [ ] All planned tasks are marked complete and the full test suite passes.
  • [ ] A completion report is generated.
  • [ ] Any rework, failed approach, or exhausted-retry blocker is recorded to

docs/lessons-learned.md as an open entry (a clean run needs none).

  • [ ] Every task was either delegated or held back by a named Keep Local

clause.

  • [ ] Delegated output passed the same tests a local implementation

would have.

  • [ ] No subsequent phase is auto-invoked (this is the terminal phase).

Related Skills

  • 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 execution
  • Skill(attune:mission-orchestrator) - Full lifecycle orchestration

Related Agents

  • Agent(attune:project-implementer) - Task execution agent

Related Commands

  • /attune:execute - Invoke this skill
  • /attune:execute --task [ID] - Execute specific task
  • /attune:execute --resume - Resume from checkpoint

Mission Report

At mission completion, produce a Mission Report using the

template from references/mission-report.md. The report documents:

  • Mission identification: Links to brief, spec, plan
  • Duration: Start, end, total time
  • Outcome: success | partial | failed
  • Delivered artifacts: Files created/modified/deleted
  • Decisions: Key choices with rationale
  • Validation evidence: Tests, reviews, demos
  • Follow-ups: Recommended next steps

See references/mission-report.md for the full template and

example reports for successful, partial, and failed missions.

Examples

See /attune:execute command documentation for complete examples.

想直接用这个技能?

本站把开放许可(MIT / Apache 等)的技能按仓库打包整理到网盘,点一下转存到你自己的网盘,不用一个个从 GitHub 拉。许可未声明的技能只给原始仓库链接,不打包。