azurekiln2333/azurekiln-ai-station-hub/trellis-check

Code Quality Check

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

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

python ./.trellis/scripts/get_context.py --mode packages

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

cat .trellis/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 .trellis/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.

Scope Discipline

• [ ] Any tidying of code the task did not require?
• [ ] Any abstraction, config or extension point added for a case that does not exist yet?
• [ ] Any speculative fallback for a state that cannot occur?
• [ ] Any file changed that the acceptance criteria do not mention?
• [ ] Any workaround added at the caller instead of a fix where the behavior actually lives?

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?

``bash grep -r "pattern" src/ ``

• [ ] If the same value repeats, does it represent one stable concept whose callers must change together? Extract only then — two literals that merely happen to match today should stay separate.
• [ ] 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?

Step 6: Report and Fix

Report every violation you find. Then:

• Mechanical and local (lint nit, missing type, wrong import, dead branch, failing assertion) → fix in place, then re-run project checks.
• Design or judgment (naming a shared concept, moving a module boundary, changing a public interface, reassigning where behavior lives) → record the evidence and your recommendation, and stop. Do not rewrite it silently.

If a fix would touch files outside the current task's scope, say so and stop instead of widening the change.