Explains how to write tests and structure test classes following stripe-android's coding standards

Mastra TypeScript framework for AI agents with memory, tools, workflows, and RAG. Use when working with @mastra/* packages or building AI agents.

Optimize for search engine visibility and ranking. Use when asked to "improve SEO", "optimize for search", "fix meta tags", "add structured data", "sitemap optimization", or "search engine optimization".

Optimize Core Web Vitals (LCP, INP, CLS) for better page experience and search ranking. Use when asked to "improve Core Web Vitals", "fix LCP", "reduce CLS", "optimize INP", "page experience optimization", or "fix layout shifts".

Comprehensive web quality audit covering performance, accessibility, SEO, and best practices. Use when asked to "audit my site", "review web quality", "run lighthouse audit", "check page quality", or "optimize my website".

Guide for upgrading Stripe API versions and SDKs

Use when working with Terraform or OpenTofu - creating modules, writing tests (native test framework, Terratest), setting up CI/CD pipelines, reviewing configurations, choosing between testing approaches, debugging state issues, implementing security scanning (trivy, checkov), or making infrastructure-as-code architecture decisions

Leverage OpenAI Codex/GPT models for autonomous code implementation. Triggers: "codex", "use gpt", "gpt-5", "let openai", "full-auto", "用codex", "让gpt实现". Use this skill whenever the user wants to delegate coding tasks to OpenAI models, run code reviews via codex, or execute tasks in a sandboxed environment.

Build multi-platform chat bots with Chat SDK (`chat` npm package). Use when developers want to (1) Build a Slack, Teams, Google Chat, Discord, GitHub, or Linear bot, (2) Use the Chat SDK to handle mentions, messages, reactions, slash commands, cards, modals, or streaming, (3) Set up webhook handlers for chat platforms, (4) Send interactive cards or stream AI responses to chat platforms, (5) Build a custom adapter for a new chat platform. Triggers on "chat sdk", "chat bot", "slack bot", "teams bot", "discord bot", "@chat-adapter", "custom adapter", "build adapter", building bots that work across multiple chat platforms.

MUST READ before writing or modifying ADK agent code. ADK API quick reference for Python — agent types, tool definitions, orchestration patterns, callbacks, and state management. Includes an index of all ADK documentation pages. Do NOT use for creating new projects (use adk-scaffold).

MUST READ before running any ADK evaluation. ADK evaluation methodology — eval metrics, evalset schema, LLM-as-judge, tool trajectory scoring, and common failure causes. Use when evaluating agent quality, running adk eval, or debugging eval results. Do NOT use for API code patterns (use adk-cheatsheet), deployment (use adk-deploy-guide), or project scaffolding (use adk-scaffold).

ALWAYS ACTIVE — read at the start of any ADK agent development session. ADK development lifecycle and mandatory coding guidelines — spec-driven workflow, code preservation rules, model selection, and troubleshooting.

MUST READ before creating or enhancing any ADK agent project. Use when the user wants to build a new agent (e.g. "build me a search agent") or enhance an existing project (e.g. "add CI/CD to my project", "add RAG").

Use when generating performance hypotheses backed by git history and code evidence.

Use when mapping code paths, entrypoints, and likely hot files before profiling.

Use when running performance benchmarks, establishing baselines, or validating regressions with sequential runs. Enforces 60s minimum runs (30s only for binary search) and no parallel benchmarks.

Use when synthesizing perf findings into evidence-backed recommendations and decisions.

Use when profiling CPU/memory hot paths, generating flame graphs, or capturing JFR/perf evidence.

Use when managing perf baselines, consolidating results, or comparing versions. Ensures one baseline JSON per version.

Use when appending structured perf investigation notes and evidence.