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Found 416 Skills
Use when a docs-driven repository request is unclear about whether the next step is scaffold initialization, clarification, roadmap decomposition, or current-task execution.
LangChain / LangGraph engineering pitfalls and verified fixes. Covers DeepAgents, OpenAI-compatible model integration (including Chinese provider adapters: DeepSeek, Qwen, GLM, etc.), middleware, streaming, multi-agent orchestration, and other common development issues. Use when hitting unexpected behavior, making architecture decisions, or integrating Chinese LLM providers during LangChain development.
Expert in designing and building autonomous AI agents. Masters tool use, memory systems, planning strategies, and multi-agent orchestration. Use when: build agent, AI agent, autonomous agent, tool use, function calling.
Build production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations. Use PROACTIVELY for LLM features, chatbots, AI agents, or AI-powered applications.
Bootstrap lean multi-agent orchestration with beads task tracking. Use for projects needing agent delegation without heavy MCP overhead.
Orchestrate multiple worker agents to implement groomed tasks. Use when multiple ready tasks need implementation, when you want autonomous multi-task execution, or when coordinating batch development work. Keywords: coordinator, orchestrator, multi-task, parallel, workers, batch, autonomous.
SPARC (Specification, Pseudocode, Architecture, Refinement, Completion) comprehensive development methodology with multi-agent orchestration
Multi-model consensus council for validation, research, and brainstorming. Spawns parallel judges with configurable perspectives and optional explorer sub-agents using runtime-native backends (Codex sub-agents or Claude teams). Modes: validate, brainstorm, research. Triggers: council, validate, brainstorm, critique, research, analyze, multi-model, consensus.
You are an expert LangChain agent developer specializing in production-grade AI systems using LangChain 0.1+ and LangGraph.
An advanced orchestration specialist that manages complex coordination of 100+ agents across distributed systems with hierarchical control, dynamic scaling, and intelligent resource allocation
Orchestrate the full Platonic Coding workflow from conceptual design to RFC specs, implementation guides, code implementation, and spec-compliance review. Always shows current phase; uses interactive chat in Phase 0, invokes platonic-specs in Phase 1, platonic-impl-guide in Phase 2, coding agents in Phase 3, and platonic-code-review in Phase 4.
Chain agents together in sequential or branching workflows with data passing