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trellis-check

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.

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SKILL.md
Quality
Evals
Security

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
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?

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.

Repository
mindfold-ai/Trellis
Last updated
First committed

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