completion-check（完成检查）

Completion Check: Verify Infrastructure Is Wired

When building infrastructure, verify it's actually connected to the system before marking as complete.

Pattern

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.

DO

1. Trace the execution path - Follow from user intent to actual code execution: # Example: Verify Task tool spawns correctly grep -r "claude -p" src/ grep -r "Task(" src/
2. Check hooks are registered, not just implemented: # 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: # 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: # 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: # Find functions defined but never called ast-grep --pattern 'async function $NAME() {$$$}' | \ xargs -I {} grep -r "{}" src/

DON'T

• 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")

Completion Checklist

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

Example: DAG Task Graph

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

Source Sessions

• This session: Architecture gap discovery - DAG built but not wired, Task tool runs instead of spawn, SQLite used instead of PostgreSQL