Results for “quality”

AI QA and evaluation specialist for quality gates. Use when the user asks to talk to Moody, requests AI evaluation, or needs regression tests for AI systems.

Creates executable Polars dataframe contracts using Pandera's Polars backend for runtime validation of schemas, columns, and checks.

Applies principles from Robert C. Martin's 'Clean Code'. Use this skill when writing, reviewing, or refactoring code to ensure high quality, readability, and maintainability. Covers naming, functio...

Identify grammar, logical, and flow errors in text and suggest targeted fixes without rewriting the entire text. Use when proofreading content, checking writing quality, or reviewing a draft.

Review local branch changes for bugs, security vulnerabilities, and code quality issues using a structured checklist-driven process.

Reviews local branch changes for bugs, security vulnerabilities, and code quality issues using a structured checklist and attack surface mapping.

Reduces cognitive complexity of a specified method by extracting logic into focused helper methods, improving readability and maintainability.

Analyzes development cycle and quality metrics to identify recurring issues, then generates additive patches to skill instructions to prevent them.

Converts Stitch designs into modular Vite and React components, using MCP networking and AST-based validation to ensure code quality.

Guides contributors through creating pull requests that add or fix skills, with a checklist covering metadata validation, risk labeling, and security disclaimers.

Routes quality reviews to specialized critic agents based on file type or flags, covering peer review, code review, and manuscript polish.

Scanpy is a scalable Python toolkit for analyzing single-cell RNA-seq data, built on AnnData. Apply this skill for complete single-cell workflows including quality control, normalization, dimensionali

Guides quality-first TDD for new behavior, bug fixes, and test changes. Selects the smallest test layer, proves a distinct regression risk, and runs bounded RED-GREEN-REFACTOR verification.

Write PHP following PSR coding standards, SOLID principles, and code-quality guidelines. Use for PHP style, design, refactoring, naming, and guard clauses—not Composer/PSR-4 project configuration.

Guide for quality focused software architecture. This skill should be used when users want to write code, design architecture, analyze code, in any case that relates to software development.

Lint and format Python with Ruff. Use when a user asks to set up Python linting, replace flake8/black/isort, configure code quality rules, or speed up Python code formatting.

Reviews REST API designs for conventions, breaking changes, and quality using automated linting and scoring tools.

Interprets shorthand, quasi-code, and natural language descriptions to produce production-quality code, bridging gaps between varying technical expertise levels.

Design a 2D floor plan and convert it into a realistic, high-quality 3D architectural rendering.

Mines git history to compute development quality, velocity, and stability metrics, compares them against stored baselines, and tracks improvement over time.

Creates interactive, publication-quality charts with 40+ types, hover tooltips, zoom, and web-embeddable exports for dashboards and exploratory analysis.

Verifica que una implementación cumpla los specs del ciclo SDD ejecutando tests reales, revisando cobertura y emitiendo un veredicto de aprobación o rechazo.

Reviews local branch changes for bugs, security vulnerabilities, and code quality issues, using a structured checklist and verification process.

Verifies test effectiveness by introducing small bugs into production code and running the test suite to find weak or missing tests.

Enforces running verification commands and confirming output before claiming work is complete, fixed, or passing, ensuring evidence precedes any success claims.

Audits a repository for comment coverage and brings under-commented source files up to standard, one file at a time, with a resumable tracker.

Tones down visually aggressive or overstimulating designs, reducing intensity while preserving quality. Use when the user mentions too bold, too loud, overwhelming, aggressive, garish, or wants a calmer, more refined aesthetic.

Tones down visually aggressive or overstimulating designs, reducing intensity while preserving quality. Use when the user mentions too bold, too loud, overwhelming, aggressive, garish, or wants a calmer, more refined aesthetic.

Use when formatting, linting, or type-checking standalone Python files that are not governed by a repository toolchain. Do not use for pyproject.toml or repository-level tooling work.

Orchestrate expensive frontier models as reviewers and cheaper subagents for bounded, token-heavy work to optimize cost and quality.

Review UI implementations against design quality standards and design system compliance, or create distinctive, production-grade frontend interfaces from scratch.

Transforms working code into clean, readable, and maintainable code following Robert C. Martin's principles.

Prevents AI agents from calling methods, imports, or variables that do not provably exist in the user's installed version, reducing hallucinated code.

Applies four disciplined mindsets—audit, debt, help, review—to cut complexity, track deferrals, surface reference, and catch over-engineering in codebases.

Optimizes agent context setup by structuring rules, specs, source files, error output, and conversation history to improve output quality.

Provides a rigorous thinking partner profile that challenges assumptions, calibrates claims to evidence, and improves decision quality under uncertainty.