/ai--multi-agent

/ai--multi-agent is a Claude Code skill in the AI & Agents section. Designs a system of several AI agents with an orchestration pattern, contracts between agents and failure handling, or advises a single agent instead.

Author's description

Design multi-agent systems: orchestrator patterns, handoffs, shared state, failure modes

How to ask for it

/ai--multi-agent design an orchestrator that splits work across agents
/ai--multi-agent how do I hand off a conversation between two agents?
/ai--multi-agent what happens if one of my agents fails mid-flow

Install

curl -fsSL https://raw.githubusercontent.com/sgomez-dev/claude-skills/main/install.sh | bash

After installing with the script, type /ai--multi-agent. Using Cursor, Windsurf or Codex? Platform guides

Demo coming soon

/ai--prompt-engineerBetter AI prompts
Reviews and rewrites your system prompts, user prompts and tool definitions, then gives an A/B comparison of the original and improved versions.
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/ai--rag-evalRAG pipeline evaluation
Builds a test harness that measures a RAG pipeline: a golden question set, retrieval metrics, groundedness checks and a regression gate.
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/ai--semantic-cacheSemantic cache for LLM calls
Adds a cache in front of LLM calls so repeated or near-duplicate requests get a stored answer, and measures whether it helps without serving wrong ones.
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/ai--structured-outputReliable LLM structured output
Makes a model return dependable JSON or typed objects: schema design, native structured modes, validation and bounded repair loops.
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/ai--tool-callingLLM tool calling
Audits or implements the tools a model can call: clear schemas, parallel calls, error handling that lets the model recover, and an accuracy eval.
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/ai--voice-agentReal-time voice agent
Designs a low-latency voice agent that handles interruptions: speech-to-text and text-to-speech choice, latency budget and conversation design.
Built here

How to ask for it

Install

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