completion-check

name	completion-check
description	Completion Check: Verify Infrastructure Is Wired
user-invocable	false

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 .maestro/hooks/my-hook.sh
   
   # Hook registered in settings?
   grep "my-hook" .maestro/settings.json
   

3. Verify database connections - Ensure infrastructure uses the right backend:

   # Check connection strings
   grep -r "sqlite:///" src/
   grep -r "duckdb" src/
   

4. Test end-to-end - Run the feature and verify infrastructure is invoked:

   # Add debug logging
   echo "DEBUG: UnifiedStorageBackend initialized" >> /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 .maestro/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