Results for “quality”

Performs a final quality pass fixing alignment, spacing, consistency, and micro-detail issues before shipping. Use when the user mentions polish, finishing touches, pre-launch review, something looks off, or wants to go from good to great.

Use when designing or building any user interface to ensure consistency, usability, and visual quality across all user-facing applications. This skill provides core UI/UX principles and standards for the enterprise ecosystem.

Performs a final quality pass fixing alignment, spacing, consistency, and micro-detail issues before shipping. Use when the user mentions polish, finishing touches, pre-launch review, something looks off, or wants to go from good to great.

Guides the creation of high-quality MCP servers that enable LLMs to interact with external services through well-designed tools, covering planning, implementation, testing, and evaluation.

Provides best practices for developing high-quality Spring Boot applications, covering project structure, dependency injection, configuration, web layer, service layer, data layer, logging, testing, and security.

Build production-quality Model Context Protocol (MCP) servers in C#/.NET using the official 1.x NuGet packages, covering transports, tools, prompts, resources, and common pitfalls.

Apply the Aesthetic-Usability Effect to ensure visual consistency and polish translate into user trust and perceived quality without masking genuine usability problems.

Defines a structured eval-driven development workflow with define, implement, and verify phases, including capability, behavior, and non-functional checks, plus optional swarm mode for parallel evaluation.

Schema validation for notes. Checks against domain-specific templates. Validates required fields, enum values, description quality, and link health. Non-blocking — warns but doesn't prevent capture. Triggers on "/validate", "/validate [note]", "check schema", "validate note", "validate all".

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, dimensionality reduction, clustering, marker gene identification, visualization, and trajectory analysis.

Turns product strategy into a production-grade MVP or shipped full-stack application using Next.js, Supabase, and Vercel with disciplined scope and quality standards.

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, dimensionality reduction, clustering, marker gene identification, visualization, and trajectory analysis.

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, dimensionality reduction, clustering, marker gene identification, visualization, and trajectory analysis.

Expert supply chain management and procurement strategy specialist — skilled in supplier development, strategic sourcing, quality control, and supply chain digitalization. Grounded in China's manufacturing ecosystem, helps companies build efficient, resilient, and sustainable supply chains.

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, dimensionality reduction, clustering, marker gene identification, visualization, and trajectory analysis.

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, dimensionality reduction, clustering, marker gene identification, visualization, and trajectory analysis.

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, dimensionality reduction, clustering, marker gene identification, visualization, and trajectory analysis.

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, dimensionality reduction, clustering, marker gene identification, visualization, and trajectory analysis.

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, dimensionality reduction, clustering, marker gene identification, visualization, and trajectory analysis.

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, dimensionality reduction, clustering, marker gene identification, visualization, and trajectory analysis.

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, dimensionality reduction, clustering, marker gene identification, visualization, and trajectory analysis.

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, dimensionality reduction, clustering, marker gene identification, visualization, and trajectory analysis.

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, dimensionality reduction, clustering, marker gene identification, visualization, and trajectory analysis.

Runs a multi-phase verification pipeline including build, type-check, lint, tests, security scan, and diff review to ensure code quality before creating a PR.

Applies universal TypeScript, JavaScript, React, and Node.js quality conventions for this repo. Use when reviewing or writing TS/TSX, refactoring for clarity, or enforcing naming, immutability, and error-handling patterns.

Create interactive, publication-quality visualizations with 40+ chart types, hover, zoom, pan, and web embedding. Choose between Plotly Express and Graph Objects for dashboards, exploratory analysis, and presentations.

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, dimensionality reduction, clustering, marker gene identification, visualization, and trajectory analysis.

Configure Maven, Gradle, and static analysis for Java projects. Use for Java-only build and quality tooling such as Spotless, Checkstyle, SpotBugs, SonarLint, JDK versions, and Java service Dockerfiles; defer Kotlin, Android, Flutter, and GitHub Actions-specific configuration.

Build or upgrade web forms to production quality: accessible structure, schema-driven validation, client↔server parity. Use when "improve this form", "form validation", "accessible form", "multi-step form", "form error handling", or "the form UX is bad".

Use when profiling, diagnosing, or improving Three.js or WebGL game performance without regressing gameplay—frame-time drops, CPU/GPU pressure, draw calls, texture/geometry budgets, animation loops, adaptive quality, mobile performance, and browser performance verification.

Uses a multi-agent generator-evaluator feedback loop to build high-quality applications from a single prompt, inspired by GANs and Anthropic's harness design.

Reduces SOC alert fatigue by tuning detection rules, consolidating duplicate alerts, implementing risk-based alerting, and measuring alert quality metrics to maintain analyst effectiveness.

Model software around the business domain using bounded contexts, aggregates, and ubiquitous language, with scoring and diagnostic tools for evaluating domain model quality.

Guides the creation of high-quality MCP servers that let LLMs interact with external services through well-designed tools, covering planning, implementation, testing, and evaluation.

Create interactive, publication-quality visualizations with 40+ chart types, including scatter, bar, line, 3D, maps, and financial charts, with support for hover, zoom, pan, subplots, and export to HTML or static images.

Review PostgreSQL code for best practices, anti-patterns, and quality standards including JSONB, arrays, custom types, schema design, functions, and security features like Row Level Security.