trellis-check

name	trellis-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 ./.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?

  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?

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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.