> browse/registry

> gatus

Expert guidance for Gatus, the lightweight, self-hosted health check and status page tool written in Go. Helps developers set up endpoint monitoring with conditions, alerting, and a beautiful status page — all configured via a single YAML file with no database required.

> gcp-bigquery

Analyze massive datasets with Google BigQuery. Run SQL queries on petabytes of data, load and stream data in real-time, create materialized views, and use BigQuery ML for machine learning models directly in SQL.

> ai-eval-ci

Run AI agent and LLM evaluations in CI/CD pipelines — automated quality gates that fail the build when AI output quality drops. Use when someone asks to "test my AI agent", "add evals to CI", "catch prompt regressions", "compare models", "evaluate LLM output quality", "set up AI quality gates", or "benchmark my agent before deploying". Covers eval frameworks (Cobalt, Promptfoo, Braintrust), LLM-as-judge scoring, threshold-based assertions, and GitHub Actions integration.

> gdpr-compliance

Automate GDPR and privacy compliance for web applications. Use when someone asks to "make the app GDPR compliant", "add cookie consent", "handle data deletion requests", "audit PII", "data subject access request", or "privacy policy generator". Covers PII auditing, consent management, data subject request endpoints, retention policies, and privacy policy generation.

> mcp-sdk

You are an expert in MCP (Model Context Protocol), the open standard by Anthropic for connecting AI models to external tools and data sources. You help developers build MCP servers that expose tools, resources, and prompts to any MCP-compatible client (Claude Desktop, Cursor, Windsurf, Cline, Continue) — creating a universal plugin system for AI assistants.

> marketing-ops-sop-generator

Generates standard operating procedures for B2B SaaS marketing operations: campaign naming conventions, UTM governance, tool administration, workflow QA, data hygiene, lead routing, and incident response playbooks. Use when setting up or auditing marketing ops processes, onboarding a new marketing ops hire, standardizing campaign tracking, fixing broken lead routing, cleaning up HubSpot or CRM data, building QA checklists for campaign launches, or creating incident response procedures for market

> mcp-server-builder

Build Model Context Protocol (MCP) servers that connect AI agents to external services and data sources. Use when a user asks to create an MCP server, build an MCP tool, connect an AI agent to an API, create a tool server for Claude, build MCP resources, or expose a database/service via MCP. Generates TypeScript or Python MCP servers with tools, resources, and prompts following the official MCP specification.

> jaeger

Deploy and use Jaeger for distributed tracing across microservices. Use when a user needs to set up trace collection, instrument applications with OpenTelemetry, analyze trace data to find latency bottlenecks, or configure Jaeger storage backends and sampling strategies.

> ragas

Expert guidance for Ragas, the framework for evaluating Retrieval-Augmented Generation pipelines. Helps developers measure and improve the quality of their RAG systems across retrieval accuracy, answer faithfulness, and response relevance.

> encore

Build cloud backend applications with Encore — type-safe backend framework with built-in infrastructure. Use when someone asks to "build a backend", "Encore", "type-safe API framework", "backend with built-in infra", "auto-provision cloud resources", or "backend framework with databases built-in". Covers API definition, databases, pub/sub, cron, and auto-provisioned infrastructure.

> opa

Expert guidance for OPA (Open Policy Agent), the CNCF policy engine for unified authorization across the stack. Helps developers write Rego policies for Kubernetes admission control, API authorization, infrastructure-as-code validation, and data filtering — enforcing security policies as code.

> langsmith

Monitor, trace, debug, and evaluate LLM applications with LangSmith. Use when a user asks to trace LLM calls, debug chain executions, evaluate AI output quality, set up LLM observability, monitor agent performance, run prompt experiments, compare model outputs, create evaluation datasets, track token usage and latency, or build LLM testing pipelines. Covers tracing, datasets, evaluators, annotation queues, prompt hub, and production monitoring.

> opentelemetry

Assists with instrumenting applications using OpenTelemetry for distributed tracing, metrics, and logs. Use when adding observability, configuring auto-instrumentation, building custom spans, setting up OTel Collectors, or exporting telemetry to Jaeger, Grafana, or Datadog. Trigger words: opentelemetry, otel, tracing, spans, metrics, observability, collector.

> go-echo

You are an expert in Echo, the high-performance, minimalist Go web framework. You help developers build REST APIs and web applications using Echo's optimized router, middleware chain, data binding, validation, template rendering, and WebSocket support — providing a clean API surface with excellent performance and comprehensive built-in middleware.

> checkov

Expert guidance for Checkov, the static analysis tool for infrastructure-as-code that scans Terraform, CloudFormation, Kubernetes, Helm, Dockerfile, and ARM templates for security misconfigurations and compliance violations. Helps developers integrate Checkov into CI/CD pipelines and write custom policies.

> schema-markup

When the user wants to add, fix, or optimize schema markup and structured data on their site. Also use when the user mentions "schema markup," "structured data," "JSON-LD," "rich snippets," "schema.org," "FAQ schema," "product schema," "review schema," or "breadcrumb schema." For broader SEO issues, see seo-audit.

> grafana

Grafana is an open-source visualization and dashboarding platform that connects to dozens of data sources including Prometheus, PostgreSQL, ClickHouse, and Elasticsearch. It lets you build interactive dashboards with panels, set up alerting rules, and manage everything as code through JSON dashboard definitions and provisioning configuration.

> graphql

Build and consume GraphQL APIs. Use when a user asks to create a GraphQL server, write GraphQL schemas, implement resolvers, set up subscriptions, build a GraphQL API, add authentication to GraphQL, optimize queries with DataLoader, implement pagination, handle file uploads, generate types from schema, consume a GraphQL endpoint, or migrate from REST to GraphQL. Covers Apollo Server, Apollo Client, schema design, resolvers, subscriptions, federation, and production patterns.

> great-expectations

Great Expectations is a Python framework for data quality testing and validation. Learn to define expectations, create validation suites, build data docs, and integrate with data pipelines for automated quality checks.

> schema-versioning

Set up and manage database schema versioning with migration files, automated rollback capabilities, and CI/CD integration. Use when you need to version database changes, generate migration files from schema diffs, safely roll back failed deployments, or audit schema history. Trigger words: migration, schema change, rollback, database versioning, ALTER TABLE, Prisma migrate, Knex migrations, Flyway, Liquibase.