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Found 13,135 Skills
CrewAI agent design and configuration. Use when creating, configuring, or debugging crewAI agents — choosing role/goal/backstory, selecting LLMs, assigning tools, tuning max_iter/max_rpm/max_execution_time, enabling planning/code execution/delegation, setting up knowledge sources, using guardrails, or configuring agents in YAML vs code.
Build and deploy AI agents with CloudBase Agent SDK (TypeScript & Python). Implements the AG-UI protocol for streaming agent-UI communication. Use when deploying agent servers, using LangGraph/LangChain/CrewAI adapters, building custom adapters, understanding AG-UI protocol events, or building web/mini-program UI clients. Supports both TypeScript (@cloudbase/agent-server) and Python (cloudbase-agent-server via FastAPI).
Sets up and operates Airbyte Agent Connectors — strongly typed Python packages for accessing 51+ third-party SaaS APIs through a unified entity-action interface. Supported services include Salesforce, HubSpot, Stripe, GitHub, Slack, Jira, Shopify, Zendesk, Google Ads, Notion, Linear, Intercom, Gong, and 36 more connectors spanning CRM, billing, payments, e-commerce, marketing, analytics, project management, helpdesk, developer tools, HR, and communication platforms. Make sure to use this skill when the user wants to connect to any SaaS API, install an airbyte-agent connector package, integrate third-party service data into a Python application or AI agent, query or search records from any supported service, or configure Airbyte MCP tools for Claude. Covers Platform Mode (Airbyte Cloud) and OSS Mode (local Python SDK).
Senior software engineer for story execution and code implementation. Use when the user asks to talk to Amelia or requests the developer agent.
Alibaba Cloud Tablestore Agent Storage Skill. Use for building and managing Tablestore-based knowledge bases with the `tablestore-agent-storage` Python SDK. Capabilities: - Install and configure the `tablestore-agent-storage` SDK - Create, describe and list knowledge bases (with subspace and custom metadata support) - Upload local files or import OSS documents into a knowledge base - Query document status and list documents - Perform hybrid retrieval (dense vector + full-text) with metadata filtering - Set up local directory sync scripts and scheduled tasks for automatic knowledge base updates Triggers: "知识库", "tablestore", "ots", "表格存储", "agent storage", "knowledge base", "向量检索", "文档上传", "文档导入", "知识库同步", "tablestore-agent-storage", "AgentStorageClient"
Use when managing Function Compute AgentRun resources via OpenAPI (runtime, sandbox, model, memory, credentials), including creating runtimes/endpoints, querying status, and troubleshooting AgentRun workflows.
Use when running Ralph-style iterative autonomous development. Triggers on /ralph or /loop commands, when autonomous iterative development is needed, when a project has specs and an implementation plan ready for iterative execution, or when deterministic context loading with subagent delegation and dual-condition exit gates is required. Orchestrates PLANNING, BUILDING, and STATUS cycles.
Vercel agent-browser — Rust CLI for AI-driven browser automation via CDP. Use when: "agent-browser", "browse website", "automate browser", "scrape with browser", "fill form", "click button", "take screenshot", "browser automation", "headless chrome", "web interaction", "accessibility snapshot", "browser refs". Deterministic ref-based selectors, JSON output, daemon architecture. Replaces Playwright/Puppeteer for agent workflows.
Agent skill for production-validator - invoke with $agent-production-validator
Use this skill whenever designing, building, or reviewing a command-line tool that AI agents or automation will invoke — covers non-interactive flags, layered --help with examples, stdin/pipeline composition, actionable errors, idempotency, dry-run, destructive-action safety, and predictable command structure. Trigger even if the user doesn't explicitly say "agent-friendly" — apply whenever they are writing `--help` text, adding a new subcommand, designing error messages, or reviewing a CLI's UX.
Cognitive Scaffolding structures an agent's context window using principles from cognitive science — primacy effects, recency bias, chunking, and attention allocation.
Use when creating, rewriting, pruning, or reviewing `AGENTS.md` or `CLAUDE.md`, especially to remove repo summaries, stale rules, and other low-signal global instructions. Trigger when deciding what belongs in always-on agent files versus a task-specific skill.