Quality

Naming Audit checks design system components, tokens, and patterns for consistency, ambiguity, and clear purpose. Use it when you need a naming review or want to find inconsistent names and rename candidates.

Receiving Code Review helps you evaluate review comments with evidence before replying or changing code. Use it after PR feedback or a code-reviewer agent to verify claims, decide what to fix, and respond technically.

Stress-tests AI-written GTM deliverables (positioning, homepage, pricing, etc.) against quality standards as a skeptical gate, so only proven work reaches the founder. Use before presenting work or when the founder questions its strength.

Tendril Review performs a thorough review of changed files in the working tree or a branch. Use it after a big change to find code smells, missing tests, broken tests, and cleanup opportunities.

Test Driven Development guides writing a failing test before production code, then making it pass and refactoring safely. Use it when implementing features or fixes, or when a hook or workflow requires test-first discipline.

Optimize your dev tool's first-run experience to get developers to their first real win quickly. Reduces friction so they activate and return.

Verification enforces evidence-based checks before you say work is done. Use it before commits, PRs, handoffs, or any completion claim.

Anti-Slop detects and removes generic AI-generated patterns in text, code, and design. Use it to review AI output, clean up content, and enforce more specific quality standards.

Debugging Skills Discovery automatically loads debugging and profiling guidance for tasks involving breakpoints, stack traces, memory leaks, core dumps, and performance analysis. Use it when you need to route into the right debugging or observability skill.

MATLAB Debugging Coach guides learners through debugging by collecting evidence, localizing the failure, and testing small repairs. Use it for error interpretation, shape and indexing mistakes, incorrect outputs, and guided repair practice.

MATLAB Hands-On Exercises guides learners through runnable MATLAB scripts for tracing, debugging, refactoring, testing, and small projects. It is used when a tutor should run code in MATLAB, compare outputs, and give feedback on correctness and style.

MATLAB Tutor Evaluation reviews MATLAB tutoring transcripts, prompts, exercises, and feedback for accuracy, active learning, guardrails, debugging support, and transfer. Use it when auditing tutor behavior or writing instructor-facing quality reports.