Results for “quality”

Benchmark AI skill effectiveness by measuring implementation quality against legacy constraints.

Provides real-time structural code health scores via CodeScene MCP to review code quality before edits, verify score deltas after changes, and gate commits and PRs.

Review code for AEM Edge Delivery Services projects, validating code quality, performance, accessibility, and adherence to EDS best practices during self-review or pull request review.

Reduces AI API costs by 30-75% by classifying task complexity, checking prompt quality, and routing tasks to the most cost-efficient model tier before execution.

Audits Claude skills and commands for quality, offering Quick Scan for changed skills and Full Stocktake modes with sequential subagent batch evaluation.

Runs a structured quality control audit on codebases, covering tests, imports, static analysis, type checking, smoke tests, UI verification, file consistency, and documentation, producing a PASS/WARN/FAIL report.

Analyzes content quality and E-E-A-T signals, scores readability, keyword use, structure, and AI citation readiness, and flags thin or outdated content.

Run technical quality checks across accessibility, performance, theming, responsive design, and anti-patterns. Generates a scored report with P0-P3 severity ratings and actionable plan. Use when the user wants an accessibility check, performance audit, or technical quality review.

Run technical quality checks across accessibility, performance, theming, responsive design, and anti-patterns. Generates a scored report with P0-P3 severity ratings and actionable plan. Use when the user wants an accessibility check, performance audit, or technical quality review.

Scans a codebase for security, database, deployment, code quality, AI/LLM, dependency, frontend, and observability issues before deployment. Intercepts deploy commands and blocks until critical items pass.

Provides ISO 13485 internal audit methodology for medical device quality management systems, covering audit planning, execution, nonconformity classification, and external audit preparation.

Orchestrate autonomous AI development pipelines through your Kanban board, managing multi-worker Claude Code dispatch, deterministic quality gates, adversarial review, per-task cost tracking, and crash-proof pipeline execution.

Enforce code quality with Ruff in a controlled, iterative workflow: run checks with optional scope and rule overrides, apply safe and unsafe autofixes, review diffs, and resolve remaining findings.

Process and analyze high-throughput sequencing data with deepTools for quality control, normalization, comparison, and publication-quality visualizations of ChIP-seq, RNA-seq, and ATAC-seq experiments.

Runs and writes tests for a project, supporting unit, integration, and end-to-end scopes, plus two-pass TDD orchestration with quality-gate checks and regression sweeps.

Runs a broad SEO audit across technical SEO, on-page SEO, schema, sitemaps, content quality, AI search readiness, and GEO, orchestrating specialized sub-skills and subagents.

Configure Kotlin build and quality tooling, including Gradle Kotlin DSL, Version Catalogs, KMP, ktlint, Detekt, MockK, coverage, and quality plugins. Use for Kotlin-specific build, lint, test-tool, or coverage setup; defer Java-only tooling and Spring test behavior.

Use before delivering any work product to validate quality. This skill provides a standardized checklist that every agent must complete before marking work as done, ensuring consistent quality across all deliverables regardless of agent or company.

Systematic workflow for verifying bug fixes to ensure quality and prevent regres...

Automated test validation, coverage checking, and quality metrics with aggressive defaults

Analyze product health across acquisition, activation, engagement, retention, quality, and monetization.

Data quality audit on CRM with completeness scoring and specific fix recommendations

Coordinates quality assurance workflows by routing testing tasks to specialized sub-skills for API testing, performance benchmarking, test analysis, tool evaluation, and process optimization.

Analyzes a single web page for on-page SEO, content quality, technical meta tags, schema, images, and performance, producing a score card and prioritized recommendations.

Review MATLAB code for quality, performance, maintainability, and adherence to MathWorks coding standards. Uses check_matlab_code and matlab_coding_guidelines. Use when reviewing code, checking style, finding code smells, assessing quality, or preparing code for handoff or publication.

GPU-accelerated data curation for LLM training, supporting text, image, video, and audio with fuzzy deduplication, quality filtering, semantic deduplication, PII redaction, and NSFW detection.

Runs a broad SEO audit covering technical SEO, on-page SEO, schema, sitemaps, content quality, AI search readiness, and GEO, with a weighted health score and prioritized action plan.

Coordinates five specialized coding agents (linter, perf, refactor, security, test) to enforce quality gates across the development lifecycle, from lint enforcement through performance profiling, refactoring, security auditing, and test coverage.

Code review automation for TypeScript, JavaScript, Python, Go, Swift, Kotlin. Analyzes PRs for complexity and risk, checks code quality for SOLID violations and code smells, generates review reports. Use when reviewing pull requests, analyzing code quality, identifying issues, generating review checklists.

Benchmark-relative quality gate. Scores the draft against the research dossier's beat spec (depth, consensus coverage, evidence) plus AI-tell and voice signals, runs an adversarial read armed with the SERP benchmark, and emits the verdict that gates the pipeline.

Create distinctive, production-grade frontend interfaces with high design quality. Covers design thinking, typography pairing, color theory, motion design, spatial composition, and code quality. Generates real working code — HTML/CSS/JS or React — with intentional aesthetic direction, not generic AI output.

Conducts multi-axis code review. Use before merging any change. Use when reviewing code written by yourself, another agent, or a human. Use when you need to assess code quality across multiple dimensions before it enters the main branch.

Manually improve corpus quality by adding missing docs and filling retrieval gaps

Decide whether an article deserves publication through hard checks and skeptical comparison.

Design and format publication-quality tables: column order, row grouping, notes, precision, reproducibility.

Performs a comprehensive cross-artifact QA/QC review of a virtual team pipeline, checking completeness, consistency, security, and compliance, then issues an advisory verdict with quality, compliance, and sign-off reports.