completion-check

SKILL.md

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

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/

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

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

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

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