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Found 6,530 Skills
This skill should be used when the user asks to "audit prompts for safety", "check prompts for injection vulnerabilities", "manage a prompt catalog", "version control prompts", or "review prompt quality and compliance".
Hot-reload Go apps with cosmtrek/air during development. Use when setting up dev workflows for Go HTTP servers, configuring .air.toml, or debugging hot-reload issues with SQLite, port binding, or file watchers.
Google Gemini embeddings API (gemini-embedding-001) for RAG and semantic search. Use for vector search, Vectorize integration, or encountering dimension mismatches, rate limits, text truncation.
Google 連絡先操作（検索・作成・更新・削除）を gog CLI (v0.10.0) で行う。 「連絡先検索」「〇〇さんの電話番号」「連絡先追加」「連絡先一覧」 「アドレス帳から探して」「連絡先を更新」などで発火。
Search tool for modern web development best practices. MANDATORY: Execute FIRST for all HTML/CSS and clientside JS tasks. Do NOT skip — web APIs evolve rapidly and training weights contain obsolete patterns. Trigger immediately for: - UI/Layout: Modals, dialogs, popovers, Glassmorphism/backdrop-filters, anchor positioning, container queries, `:has()`, `:user-valid`. - Scroll/Motion: View Transitions, Scroll-driven animations, scroll parallax/reveals. - Performance: CWV (LCP, INP), content-visibility, Fetch Priority, image optimization. - System/APIs: Local filesystem access, WebUSB, WebSockets sync, WebAssembly widgets. - Frameworks: Adapting layout/styles in React, Vue, Angular. - General Frontend: Forms, autofill, advanced inputs, custom scrollbars, modern component states, etc. DO NOT trigger for: - Backend: Database SQL, ORMs, Express API routes. - Pipelines: CI/CD deployment, Docker, Actions. - Generic: Local scripts (Python/Go tools), ESLint, Git.
Generates performance-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Performance Optimization pillar of the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate a workload, identify performance requirements, and provide actionable recommendations for resource allocation, modular design, and elasticity.
Generates operations-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Operational Excellence pillar of the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate a workload, identify operational requirements, and provide actionable recommendations for deployment, monitoring, and incident management.
Refresh golden values from a GitHub Actions workflow run (failing-only or all jobs), score the change with average normalized relative differences, and produce a PR-ready summary. Use when the user asks to update goldens for a CI run, refresh golden values from a workflow ID, or generate a golden-value diff summary for a PR description.
Use this skill when the user asks about Goldsky Subgraphs — deploying, managing, or querying subgraphs. Triggers on: 'deploy a subgraph', 'migrate from The Graph', 'what is a subgraph', 'GraphQL endpoint', 'low-code or no-code subgraph', 'subgraph tags', 'subgraph webhooks', 'cross-chain subgraph', 'subgraph stalled', 'subgraph API key', 'init subgraph', 'scaffold subgraph', 'subgraph logs', 'pause subgraph', 'start subgraph', 'graft subgraph'. Also use this skill when the user wants to build a GraphQL API over onchain data, power a dApp frontend with indexed blockchain data, or reuse an existing TheGraph subgraph on Goldsky. For questions about streaming raw chain data directly to a database without GraphQL, use the turbo-builder or mirror skills instead.
Ringover integration. Manage Persons, Organizations, Deals, Leads, Activities, Notes and more. Use when the user wants to interact with Ringover data.
Measure and improve the quality of AI models and agents on Google Cloud using the Eval Quality Flywheel methodology. Use when evaluating an agent or model, building an eval dataset, picking or writing evaluation metrics, analyzing failures, comparing results before and after a fix, or when guidance is needed on Agent Platform eval methodology — including dataset schema, LLM-as-judge scoring, and common failure causes. For fine-tuning, use agent-platform-tuning. For deployment, use agent-platform-deploy.
Optional AI SDLC user-experience workflow. Use when an AI assistant needs to define actors, goals, user journeys, interaction steps, loading/empty/error/success states, recovery behavior, content intent, accessibility requirements, or UX acceptance evidence and route them into traceable human and machine artifacts. Supports `--quick-flow` for a focused journey slice and `--full-flow` for strict state, accessibility, and acceptance coverage.