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completion-check

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Original

English
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Translation

Chinese

Completion Check: Verify Infrastructure Is Wired

完成检查：验证基础设施已正确接入

When building infrastructure, verify it's actually connected to the system before marking as complete.
在构建基础设施时，需先验证其已实际接入系统，再标记为完成。

Pattern

模式

Infrastructure is not done when the code is written - it's done when it's wired into the system and actively used. Dead code (built but never called) is wasted effort.
基础设施并非代码写完就完成——只有当它接入系统并被主动使用时才算完成。死代码（已构建但从未被调用）是无用的付出。

DO

应该做

  1. Trace the execution path - Follow from user intent to actual code execution:
    bash
    # Example: Verify Task tool spawns correctly
grep -r "claude -p" src/
grep -r "Task(" src/
  2. Check hooks are registered, not just implemented:
    bash
    # Hook exists?
ls -la .claude/hooks/my-hook.sh

# Hook registered in settings?
grep "my-hook" .claude/settings.json
  3. Verify database connections - Ensure infrastructure uses the right backend:
    bash
    # Check connection strings
grep -r "postgresql://" src/
grep -r "sqlite:" src/  # Should NOT find if PostgreSQL expected
  4. Test end-to-end - Run the feature and verify infrastructure is invoked:
    bash
    # Add debug logging
echo "DEBUG: DAG spawn invoked" >> /tmp/debug.log

# Trigger feature
uv run python -m my_feature

# Verify infrastructure was called
cat /tmp/debug.log
  5. Search for orphaned implementations:
    bash
    # Find functions defined but never called
ast-grep --pattern 'async function $NAME() { $$$ }' | \
  xargs -I {} grep -r "{}" src/
  1. 追踪执行路径——从用户意图到实际代码执行全程追踪：
    bash
    # Example: Verify Task tool spawns correctly
grep -r "claude -p" src/
grep -r "Task(" src/
  2. 检查钩子已注册，而非仅实现：
    bash
    # Hook exists?
ls -la .claude/hooks/my-hook.sh

# Hook registered in settings?
grep "my-hook" .claude/settings.json
  3. 验证数据库连接——确保基础设施使用正确的后端：
    bash
    # Check connection strings
grep -r "postgresql://" src/
grep -r "sqlite:" src/  # Should NOT find if PostgreSQL expected
  4. 端到端测试——运行功能并验证基础设施已被调用：
    bash
    # Add debug logging
echo "DEBUG: DAG spawn invoked" >> /tmp/debug.log

# Trigger feature
uv run python -m my_feature

# Verify infrastructure was called
cat /tmp/debug.log
  5. 查找孤立实现：
    bash
    # Find functions defined but never called
ast-grep --pattern 'async function $NAME() { $$$ }' | \
  xargs -I {} grep -r "{}" src/

DON'T

不应该做

  • Mark infrastructure "complete" without testing execution path
  • Assume code is wired just because it exists
  • Build parallel systems (Task tool vs claude -p spawn)
  • Use wrong backends (SQLite when PostgreSQL is architected)
  • Skip end-to-end testing ("it compiles" ≠ "it runs")
  • 未测试执行路径就标记基础设施“已完成”
  • 仅因代码存在就假设已接入系统
  • 构建并行系统（Task工具 vs claude -p 启动）
  • 使用错误的后端（架构设计为PostgreSQL却用SQLite）
  • 跳过端到端测试（“能编译”≠“能运行”）

Completion Checklist

完成检查清单

Before declaring infrastructure complete:
  • Traced execution path from entry point to infrastructure
  • Verified hooks are registered in .claude/settings.json
  • Confirmed correct database/backend in use
  • Ran end-to-end test showing infrastructure invoked
  • Searched for dead code or parallel implementations
  • Checked configuration files match implementation
在宣布基础设施完成前：
  • 追踪从入口点到基础设施的执行路径
  • 验证钩子已在.claude/settings.json中注册
  • 确认使用了正确的数据库/后端
  • 运行端到端测试，证明基础设施已被调用
  • 搜索死代码或并行实现
  • 检查配置文件与实现是否匹配

Example: DAG Task Graph

示例：DAG任务图

Wrong approach:
✓ Built BeadsTaskGraph class
✓ Implemented DAG dependencies
✓ Added spawn logic
✗ Never wired - Task tool still runs instead
✗ Used SQLite instead of PostgreSQL
Right approach:
✓ Built BeadsTaskGraph class
✓ Wired into Task tool execution path
✓ Verified claude -p spawn is called
✓ Confirmed PostgreSQL backend in use
✓ Tested: user calls Task() → DAG spawns → beads execute
✓ No parallel implementations found
错误做法：
✓ Built BeadsTaskGraph class
✓ Implemented DAG dependencies
✓ Added spawn logic
✗ Never wired - Task tool still runs instead
✗ Used SQLite instead of PostgreSQL
正确做法：
✓ Built BeadsTaskGraph class
✓ Wired into Task tool execution path
✓ Verified claude -p spawn is called
✓ Confirmed PostgreSQL backend in use
✓ Tested: user calls Task() → DAG spawns → beads execute
✓ No parallel implementations found

Source Sessions

来源会话

  • This session: Architecture gap discovery - DAG built but not wired, Task tool runs instead of spawn, SQLite used instead of PostgreSQL
  • 本次会话：架构缺口发现——DAG已构建但未接入，Task工具仍在运行而非启动，使用SQLite而非PostgreSQL