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Expert husky capability pack for lightweight local quality gates, commit message enforcement, and low-friction contributor workflows.

Expert OpenClaw skill-authoring capability pack for repeatable research, validation, packaging, and distribution workflows.

Create useful Gemini-powered Google Workspace automations for docs, sheets, email triage, and internal workflow productivity.

Design and validate model routing strategies that reduce cost and latency while preserving output quality.

Expert Raycast extension capability skill for command design, extension architecture, testing, and store-ready publication workflows.

Access high-quality fundamental financial data from SEC filings and investor presentations

The official Codacy MCP server (@codacy/codacy-mcp) that gives AI assistants access to the Codacy API for code quality, security, and coverage — listing repository and pull-request issues, retrieving file coverage and duplication, searching security (SRM) findings, inspecting analysis tools and patterns, and running local analysis with the Codacy CLI.

Connect Claude to Teradata — list databases and tables, inspect DDL, run SQL queries, preview data, analyze column quality, and explore DBA diagnostics — with the official Teradata MCP server supporting optional ML tool expansion via the teradataml Python package.

Official SonarSource MCP server that connects Claude to SonarQube Server or SonarQube Cloud for code quality, security issues, hotspots, measures, quality gates, branches, pull requests, snippets, and system context.

Apache-2.0 GX Core Python library for data quality Expectations, validation definitions, checkpoints, Data Docs, metadata stores, and pipeline quality checks.

Open-source ML and LLM observability framework for evaluating, testing, and monitoring data quality, drift, model behavior, and AI application outputs.

Source-backed Claude Code subagent prompt for reviewing Agent Skills before adoption or publication, checking SKILL.md scope, descriptions, invocation control, supporting files, tool permissions, helpfulness, safety, and privacy risks against official Claude Code skills guidance.

An agent prompt for curating an organization's Agent Skills: reviewing each SKILL.md name and description, scope (personal, project, or plugin) and precedence, per-skill allowed-tools, and whether Claude or the user invokes it.

A source-backed collection for reproducible data analysis and notebook work: Marimo notebooks, DuckDB analytical SQL, Polars DataFrames, Hugging Face Datasets loading, Great Expectations quality checks, and Streamlit sharing.

A practical guide for preparing source-backed HeyClaude content pull requests that stay focused, cite verifiable sources, avoid generated artifacts, and pass content validation.

Modern data pipeline specialist focused on real-time streaming, ETL/ELT orchestration, data quality validation, and scalable data infrastructure with Apache Airflow, dbt, and cloud-native tools

Comprehensive pre-commit hook that validates code quality, runs tests, and enforces standards.

Expert code reviewer that provides thorough, constructive feedback on code quality, security, performance, and best practices

AI testing platform for evaluating, scanning, and monitoring machine learning and LLM application quality.

An agent pattern for routing rapid-iteration work to Claude Haiku 4.5 — more than twice Sonnet's speed at one-third the cost ($1/$5 per million tokens) — while keeping about 90% of Sonnet 4.5's agentic-coding quality.

Biome linting rules configuration for code quality validation. Strict enforcement, custom overrides, VCS integration, and automated fixes for TypeScript.

A collection that bundles three Claude Code resources for code review: a code-reviewer sub-agent plus the generate-tests and explain commands.

Comprehensive system for ensuring code quality, security, and compliance before production deployment. Includes automated code reviews, complexity monitoring, backup strategies, and production-grade rules for professional development teams.

Expert in automated testing strategies, test frameworks, and quality assurance across unit, integration, and end-to-end testing

Build repeatable eval suites that catch quality regressions in AI agent behavior before merge or release.

Community slash command runbook for adding minimal automated tests around a changed module: inspect the git diff, mirror repository test conventions, and draft focused unit or integration tests using Anthropic develop-tests guidance.

Slash command runbook for designing and running prompt evaluations: define tasks, success criteria, golden outputs, regression checks, and privacy-safe reporting using Anthropic test-and-evaluate guidance.

Claude Code session health aggregator providing A-F grade based on cost efficiency, latency performance, productivity velocity, and cache utilization with actionable recommendations.

A user-created custom slash command that runs a red-green-refactor TDD loop in Claude Code: write failing tests first, implement until they pass, then refactor. Built with the documented custom-command frontmatter and $ARGUMENTS substitution, not a built-in feature.

Generates a comprehensive test coverage report when the coding session ends.