Agents
AI agents and automation
🤖 Multi-Agent Orchestration & State Management
by Dokhacgiakhoa
Created by Antigravity Orchestrator - Based on Autonomous Agent Architectures.
tensorlake
by tensorlakeai
Tensorlake SDK for agent sandboxes and sandbox-native orchestration. Use when the user mentions tensorlake, or asks about Tensorlake APIs/docs/capabilities. Also use when the user is building AI agents or agentic applications that need stateful sandboxed execution environments for agents and isolated tool calls, with suspend/resume and snapshots for persistence between tasks, or durable workflow orchestration for agents (parallel map/reduce DAGs). Works with any LLM provider (OpenAI, Anthropic), agent framework (LangChain), database, or API as the infrastructure layer.
spawn
by 0xDarkMatter
"Generate PhD-level expert agent prompts for Claude Code. Creates comprehensive 500-1000 line agents with detailed patterns, code examples, and best practices. Triggers on: spawn agent, create agent, generate expert, new agent, agent genesis."
cursor-agent-supervisor
by YPares
Offloading tasks with a well-defined scope to sub-agents, for instance to use a sub-agent to implement a set of specs. Use this skill whenever a task should not need a broad knowledge of the whole project
agent-browser
by ArabelaTso
CLI-based browser automation with persistent page state using ref-based element interaction. Use when users ask to navigate websites, interact with web pages, fill forms, take screenshots, test web applications, or extract information from web pages.
full-workflow
by terrylica
Full workflow - record + backup + convert + analyze. TRIGGERS - full workflow, complete recording, end-to-end.
post-session
by terrylica
Complete post-session workflow - finalize orphaned recordings, convert, and AI summarize. TRIGGERS - post session, analyze recording, session review, complete workflow.
pydantic-ai-tool-system
by existential-birds
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.
langgraph-architecture
by existential-birds
Guides architectural decisions for LangGraph applications. Use when deciding between LangGraph vs alternatives, choosing state management strategies, designing multi-agent systems, or selecting persistence and streaming approaches.
deepagents-implementation
by existential-birds
Implements agents using Deep Agents. Use when building agents with create_deep_agent, configuring backends, defining subagents, adding middleware, or setting up human-in-the-loop workflows.
deepagents-code-review
by existential-birds
Reviews Deep Agents code for bugs, anti-patterns, and improvements. Use when reviewing code that uses create_deep_agent, backends, subagents, middleware, or human-in-the-loop patterns. Catches common configuration and usage mistakes.
pydantic-ai-model-integration
by existential-birds
Configure LLM providers, use fallback models, handle streaming, and manage model settings in PydanticAI. Use when selecting models, implementing resilience, or optimizing API calls.
pydantic-ai-testing
by existential-birds
Test PydanticAI agents using TestModel, FunctionModel, VCR cassettes, and inline snapshots. Use when writing unit tests, mocking LLM responses, or recording API interactions.
pydantic-ai-common-pitfalls
by existential-birds
Avoid common mistakes and debug issues in PydanticAI agents. Use when encountering errors, unexpected behavior, or when reviewing agent implementations.
langgraph-implementation
by existential-birds
Implements stateful agent graphs using LangGraph. Use when building graphs, adding nodes/edges, defining state schemas, implementing checkpointing, handling interrupts, or creating multi-agent systems with LangGraph.
deepagents-architecture
by existential-birds
Guides architectural decisions for Deep Agents applications. Use when deciding between Deep Agents vs alternatives, choosing backend strategies, designing subagent systems, or selecting middleware approaches.
pydantic-ai-agent-creation
by existential-birds
Create PydanticAI agents with type-safe dependencies, structured outputs, and proper configuration. Use when building AI agents, creating chat systems, or integrating LLMs with Pydantic validation.
pydantic-ai-dependency-injection
by existential-birds
Implement dependency injection in PydanticAI agents using RunContext and deps_type. Use when agents need database connections, API clients, user context, or any external resources.
tdd-workflow
by dgalarza
Use this skill whenever you are implementing a feature using TDD.
parallel-code-review
by dgalarza
This skill should be used when performing comprehensive code reviews using multiple specialized review agents in parallel. It provides patterns for concurrent execution, decision tracking to prevent redundancy, and consolidated reporting. Use when needing thorough review coverage from multiple perspectives (security, architecture, performance) or when reviewing large changesets.
uni-agent
by zrt-ai-lab
统一智能体协议适配层。一套 API 调用所有 Agent 协议（ANP/MCP/A2A/AITP 等）。当用户需要调用 Agent、跨协议通信、连接工具时触发此技能。
salesforce
by refly-ai
"Integrate with Salesforce for CRM operations. Use when you need to: (1) create and query Salesforce records, (2) manage accounts and opportunities, or (3) automate sales workflows."
langconfig-builder
by LangConfig
"Complete guide for building agents and workflows in LangConfig. Use when users need help configuring nodes, connecting agents, setting up tools, or designing multi-agent systems within the LangConfig platform."
amazon-christmas-tree-research
by refly-ai
亚马逊圣诞树竞品调研分析，搜索热销产品，分析定价策略、用户评价和市场机会