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Found 883 Skills
Configuration Management implements dynamic configuration with hot-reload capability, inspired by Nacos configuration management patterns.
Grafana Cloud testing capabilities — Synthetic Monitoring (probing URLs, DNS, TCP, ping from multiple regions), k6 Cloud (managed load testing with distributed execution), and Frontend Observability (Faro, real user monitoring). Use when setting up uptime checks, external probes, configuring k6 cloud runs, monitoring frontend performance, or testing APIs from multiple locations.
Use when adding capabilities to an existing agent project — memory, app integration, VPC, multi-agent, migration, model changes, browser, code interpreter, or resource removal. Triggers on: "add memory", "remember across sessions", "call agent from app", "invoke agent from code", "auth to call agent", "streaming responses", "VPC", "VPC connectivity", "VPC error", "can't reach from VPC", "multi-agent", "A2A", "A2A auth", "orchestrator not delegating", "specialist not called", "migrate Bedrock Agent", "after import", "migration issue", "framework for migration", "change model", "browser tool", "code interpreter", "delete agent", "tear down", "agentcore remove", "cross-account memory", "resource-based policy on memory". Not for connecting to external APIs via Gateway — use agents-connect. Not for scaffolding a new project — use agents-get-started. Not for CLI/dev server errors — use agents-debug. Strands vs LangGraph in a migration context routes here.
Use when building Vue 3 applications with Composition API, Nuxt 3, or Quasar. Invoke for Pinia, TypeScript, PWA, Capacitor mobile apps, Vite configuration.
Package entire code repositories into single AI-friendly files using Repomix. Capabilities include pack codebases with customizable include/exclude patterns, generate multiple output formats (XML, Markdown, plain text), preserve file structure and context, optimize for AI consumption with token counting, filter by file types and directories, add custom headers and summaries. Use when packaging codebases for AI analysis, creating repository snapshots for LLM context, analyzing third-party libraries, preparing for security audits, generating documentation context, or evaluating unfamiliar codebases.
Use this skill when developing browser/Web applications (React/Vue/Angular, static websites, SPAs) that need AI capabilities. Features text generation (generateText) and streaming (streamText) via @cloudbase/js-sdk. Built-in models include Hunyuan (hunyuan-2.0-instruct-20251111 recommended) and DeepSeek (deepseek-v3.2 recommended). NOT for Node.js backend (use ai-model-nodejs), WeChat Mini Program (use ai-model-wechat), or image generation (Node SDK only).
Register and implement PydanticAI tools with proper context handling, type annotations, and docstrings. Use when adding tool capabilities to agents, implementing function calling, or creating agent actions.
Full-stack web development with Next.js and Turborepo. Stack: Next.js 14+ (App Router, RSC, Server Actions, PPR, SSR, SSG, ISR), Turborepo (monorepo, pipelines, remote caching), RemixIcon (3100+ icons). Capabilities: server components, API routes, middleware, caching strategies, build optimization, monorepo management. Actions: create, build, deploy, optimize Next.js apps, setup monorepo, configure caching. Keywords: Next.js, App Router, Server Components, RSC, Server Actions, SSR, SSG, ISR, PPR, Turborepo, monorepo, remote cache, build pipeline, parallel execution, workspace, pnpm, icons. Use when: building Next.js apps, implementing SSR/SSG, setting up monorepos, optimizing build performance, configuring caching strategies, managing shared dependencies.
Expert in load balancing and dynamic task allocation for multi-agent systems. Specializes in optimal routing based on agent capability, availability, and cost (Token Economics).
Guides users through configuring Tauri command scopes for security, including filesystem restrictions, URL patterns, dynamic scope management, and capability-based access control.
This skill should be used when conducting comprehensive research on any topic using the OpenAI Deep Research API. It automates prompt enhancement through interactive clarifying questions, saves research parameters, and executes deep research with web search capabilities. Use when the user asks for in-depth analysis, investigation, research summaries, or topic exploration.
Captures learnings, errors, and corrections to enable continuous improvement. Use when: (1) A command or operation fails unexpectedly, (2) User corrects Claude ('No, that's wrong...', 'Actually...'), (3) User requests a capability that doesn't exist, (4) An external API or tool fails, (5) Claude realizes its knowledge is outdated or incorrect, (6) A better approach is discovered for a recurring task. Also review learnings before major tasks.