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Completion Check: Verify Infrastructure Is Wired

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continuous-claude-v3
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$ npx -y skills add parcadei/Continuous-Claude-v3 --skill completion-check --agent claude-code

SKILL.md

completion-check.SKILL.md
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 .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
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Which coding agents can use completion-check?
completion-check installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.