completion-check

安装量: 182
排名: #4718

安装

npx skills add https://github.com/parcadei/continuous-claude-v3 --skill completion-check

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

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