coding-check

name	coding-check
description	Comprehensive quality verification: spec compliance, lint, type-check, tests, cross-layer data flow, code reuse, and consistency checks. Use when code is written and needs quality verification, before committing changes, or to catch context drift during long sessions.

Code Quality Check

Comprehensive quality verification for recently written code. Combines spec compliance, cross-layer safety, and pre-commit checks.

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Step 1: Identify What Changed

git diff --name-only HEAD
git status

Step 2: Read Task Artifacts and Applicable Specs

Read the current task artifacts in order:

• prd.md
• design.md if present
• implement.md if present

python3 ./.coding/scripts/get_context.py --mode packages

For each changed package/layer, read the spec index and follow its Quality Check section:

cat .coding/spec/<package>/<layer>/index.md

Read the specific guideline files referenced — the index is a pointer, not the goal.

Step 3: Run Project Checks

Run the project's lint, type-check, and test commands. Fix any failures before proceeding.

Step 4: Review Against Checklist

Code Quality

• Linter passes?
• Type checker passes (if applicable)?
• Tests pass?
• No debug logging left in?
• No suppressed warnings or type-safety bypasses?

Test Coverage

• New function → unit test added?
• Bug fix → regression test added?
• Changed behavior → existing tests updated?

Spec Sync

• Does .coding/spec/ need updates? (new patterns, conventions, lessons learned)

"If I fixed a bug or discovered something non-obvious, should I document it so future me won't hit the same issue?" → If YES, update the relevant spec doc.

Step 5: Cross-Layer Dimensions (if applicable)

Skip this step if your change is confined to a single layer.

A. Data Flow (changes touch 3+ layers)

• Read flow traces correctly: Storage → Service → API → UI
• Write flow traces correctly: UI → API → Service → Storage
• Types/schemas correctly passed between layers?
• Errors properly propagated to caller?

B. Code Reuse (modifying constants, creating utilities)

• Searched for existing similar code before creating new?

  grep -r "pattern" src/
  

• If 2+ places define same value → extracted to shared constant?
• After batch modification, all occurrences updated?

C. Import/Dependency (creating new files)

• Correct import paths (relative vs absolute)?
• No circular dependencies?

D. Same-Layer Consistency

• Other places using the same concept are consistent?

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Step 6: Report and Fix

Report violations found and fix them directly. Re-run project checks after fixes.