Results for “multi-agent”

Orchestrates three frontier models to debate a question and synthesizes their best insights into a single superior answer.

Multi-agent autonomous startup system for Claude Code. Triggers on "Loki Mode". Orchestrates 100+ specialized agents across engineering, QA, DevOps, security, data/ML, business operations,...

Call the Gemini API for text generation, chat, multimodal understanding, image/video/audio generation, streaming, function calling, structured output, and managed agents using the Interactions API in Python and TypeScript.

智能路由中心，自动识别用户意图并路由到相应技能，提供专业化的深度研究体验，支持多Agent并行调研与监控。

Expert en Ollama avancé (local LLMs, models, REST API, hardware, multi-modal, DZ deployment)

Run multiple AI agents against a product, SDK, or docs site to score setup friction, speed, efficiency, error recovery, and doc quality from a minimal prompt.

Run Claude Code autonomously in loops, from simple sequential pipelines to multi-agent DAG orchestration.

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.

Facilitates a multi-perspective discussion on Austrian economics between Hayek, Mises, and Claude, analyzing user questions through their distinct philosophical lenses.

Turns a brief product idea into working, verified code by orchestrating requirements analysis, planning, parallel implementation, QA, and multi-perspective validation.

Offload sub-tasks to other agents, specialist models, or background jobs, with guidance on choosing the right method and verifying results.

Expert in CrewAI - the leading role-based multi-agent framework used by 60% of Fortune 500 companies.

Expert in CrewAI - the leading role-based multi-agent framework used by 60% of Fortune 500 companies.

Expert in CrewAI - the leading role-based multi-agent framework used by 60% of Fortune 500 companies.

Expert in CrewAI - the leading role-based multi-agent framework used by 60% of Fortune 500 companies.

Expert in CrewAI - the leading role-based multi-agent framework used by 60% of Fortune 500 companies.

Expert in CrewAI - the leading role-based multi-agent framework used by 60% of Fortune 500 companies.

Expert in CrewAI - the leading role-based multi-agent framework used by 60% of Fortune 500 companies.

Expert in CrewAI - the leading role-based multi-agent framework used by 60% of Fortune 500 companies.

Expert in CrewAI - the leading role-based multi-agent framework used by 60% of Fortune 500 companies.

Expert in CrewAI - the leading role-based multi-agent framework used by 60% of Fortune 500 companies.

Build and review high-quality technical documentation, including agent instruction files and contributor-governance files, with support for audits, multilingual parity, and sub-agent orchestration.

ByteDance's open-source super agent harness — spawns parallel sub-agents, Docker sandbox execution, persistent long-term memory, modular skills (research/report/slides). Built on LangChain + LangGraph. Triggers on: 'deerflow', 'deer-flow', 'bytedance agent', 'super agent harness', 'LangGraph agent orchestration', 'multi-hour agent tasks', 'spawn sub-agents', 'agent sandbox docker', 'persistent agent memory', 'agent skills system', 'AI research orchestrator', 'long-running agent tasks', 'agent with memory', 'langgraph orchestrator', 'IM channel agent integration'.

Create focused role prompts for agents in multi-agent topologies. Load when agent-builder needs role prompts for agents, or when a user asks to "create an agent prompt", "write a role prompt", "define agent identity", "write an agent role", "prompt for this agent", "write instructions for this agent", "agent persona". Scope: agent role prompts only (v1). System prompts, task prompts, and skill invocation prompts are future TODOs.

Content Factory multi-agent orchestrator. Use when the user says @orchestrator, asks to divide work, run a swarm, coordinate specialists, or when the task is non-trivial (multi-file, audit, cleanup, feature, incident). ALWAYS launch 5–10 agents with clear scopes; merge results; block guesswork.

Multi-agent collaboration plugin that spawns N parallel subagents competing on the same task via git worktree isolation. Agents work independently, results are evaluated by metric or LLM judge, and the best branch is merged. Use when: user wants multiple approaches tried in parallel — code optimization, content variation, research exploration, or any task that benefits from parallel competition. Requires: a git repo.

Multi-agent collaboration plugin that spawns N parallel subagents competing on the same task via git worktree isolation. Agents work independently, results are evaluated by metric or LLM judge, and the best branch is merged. Use when: user wants multiple approaches tried in parallel — code optimization, content variation, research exploration, or any task that benefits from parallel competition. Requires: a git repo.

Multi-agent collaboration plugin that spawns N parallel subagents competing on the same task via git worktree isolation. Agents work independently, results are evaluated by metric or LLM judge, and the best branch is merged. Use when: user wants multiple approaches tried in parallel — code optimization, content variation, research exploration, or any task that benefits from parallel competition. Requires: a git repo.

Multi-agent collaboration plugin that spawns N parallel subagents competing on the same task via git worktree isolation. Agents work independently, results are evaluated by metric or LLM judge, and the best branch is merged. Use when: user wants multiple approaches tried in parallel — code optimization, content variation, research exploration, or any task that benefits from parallel competition. Requires: a git repo.

Multi-agent collaboration plugin that spawns N parallel subagents competing on the same task via git worktree isolation. Agents work independently, results are evaluated by metric or LLM judge, and the best branch is merged. Use when: user wants multiple approaches tried in parallel — code optimization, content variation, research exploration, or any task that benefits from parallel competition. Requires: a git repo.

Build LLM-powered applications with agents, chains, and RAG using a framework that supports multiple providers and 500+ integrations.

Expert in CrewAI - the leading role-based multi-agent framework used by 60% of Fortune 500 companies.

OpenProse VM skill pack. Activate on any `prose` command, .prose files, or OpenProse mentions; orchestrates multi-agent workflows.

Multi-agent collaboration plugin that spawns N parallel subagents competing on the same task via git worktree isolation. Agents work independently, results are evaluated by metric or LLM judge, and the best branch is merged. Use when: user wants multiple approaches tried in parallel — code optimization, content variation, research exploration, or any task that benefits from parallel competition. Requires: a git repo.

Automatically measures whether coding agents follow skills, rules, or agent definitions by generating scenarios at multiple prompt strictness levels, running agents, classifying tool calls, and reporting compliance rates with full timelines.

Simulates multi-expert panel discussions by recommending or accepting specified experts, generating parallel dialogues, and providing a judge summary for each round.