Results for “multi-agent”

Architecte Agent IA — Conçoit et déploie des agents IA (Hermes, Claude Code, n8n, NVIDIA NIM). Expert en architecture multi-agents, orchestration, et intégration de workflows IA.

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Autonomous CI/CD error recovery, distributed file-based locking, diagnostic triage, and two-phase GO gate resilience engine for BDB Agent OS multi-agent pipelines.

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

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Linear multi-agent build pipeline with file hand-offs in production_artifacts/, run after /bdbrainstorm or /grill-me. This is the linear variant — no state.json, no repair loop, no dispatcher graph — distinct from startcycle-graph, which adds durable state and automated escalation. Use when an approved plan should be built, when the user types /startcycle or "run a startcycle", or when you pick a startcycle variant from the situation yourself (no user prompt needed).

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AI agent development workflow for building autonomous agents, multi-agent systems, and agent orchestration with CrewAI, LangGraph, and custom agents.

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Interactive 9-step prompt crafting and delegation protocol for autonomous multi-agent teams. Enforces objective verification, integrity modes, and acceptance criteria across Antigravity, Claude Code, Cursor, OpenCode, Codex, and Roo Code.

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Use when a task needs a small, throwaway multi-agent fan-out (a couple of parallel workers plus a review pass) in ANY project — trigger phrases "spawn a few parallel agents", "fan out", "quick worker team" — without the full /startcycle-graph contract, no .agents/graph.md bootstrap, no state.json schema, no persistent files. Roles run on the session model unless `.aos/pipeline.json` overrides one (an external CLI can take the worker step) and portable across machines that may not have Antigravity/OpenCode/Codex installed.

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Use when running the autonomous multi-agent build pipeline after /bdbrainstorm or /grill-me, when the user types /startcycle-graph or "run a startcycle", or when a task needs durable state, a review repair loop and an automated quality gate. Routes to the startcycle-dispatch Dynamic Workflow, which reads production_artifacts/state.json and invokes Architect, TechLead, UI/UX, Engineering, Media/EventTech, Reviewer, and Shipping in turn per .agents/graph.md's edge table — the agents never invoke each other.

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Agent tool で複数のサブエージェントを並列起動する／エージェントチームを組成する前に、編成パターン（サブエージェント vs エージェントチーム、レビュアー Teammate の要否、各役割のモデル選択）を決定するためのガイドを適用する。トリガー：3 つ以上の Agent を並列起動する／タスク間に依存関係がある／チームメイト同士の相互通信が必要／設計や計画フェーズで複数視点が欲しい／ある成果物を別の成果物がレビュー・参照する構造になる。単発のサブエージェント呼び出しや、依存のない fire-and-forget な並列調査では発火しない。

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Multi-agent SWE team built on the Workshop model. Full-stack vertical workers, meeting room with @mention notification, private pipes, shared task board. Git worktree isolation, Leader-driven coordination. Mixed Codex/Claude Code engine. Use when a task needs engineering depth beyond a single agent. NOT for simple task parallelism (use agent-task-orchestration) or design discussions (use agent-brainstorm).

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Multi-agent brainstorming: async opinion collision with expert personas. Mixed Codex/Claude Code engine. Use when multiple AI agents need to collaboratively discuss, debate, and converge on solutions through structured dialog. Triggers: brainstorm, multi-perspective discussion, opinion collision, expert debate, war room, collective intelligence, 头脑风暴, 多视角讨论, 集思广益.

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Task decomposition and multi-agent orchestration with retry, checkpoint recovery, and real-time monitoring. Mixed Codex/Claude Code engine. Parallel/sequential execution.

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Plan and execute large refactor or rewrite efforts efficiently with parallel multi-agent analysis and implementation. Use when a user asks to refactor many files, split workstreams, analyze a target code area, and coordinate sub-agents with clear ownership and dependency-aware execution.

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Parallel read-only multi-agent review of a current git diff or explicit file scope to find behavioral regressions, security or privacy risks, performance or reliability issues, and contract or test coverage gaps. Use when the user asks for a review swarm, parallel review, diff review, regression review, security review, or wants high-signal issues plus a prioritized fix path without editing files.

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Parallel read-only multi-agent root-cause investigation for bugs, regressions, crashes, flaky behavior, or unexplained failures. Use when the user asks to investigate a bug, find the root cause, trace a regression, understand why something broke, or wants a ranked diagnosis with the fastest proof path without making code edits.

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Multi-agent orchestration patterns. Use when multiple independent tasks can run with different domain expertise or when comprehensive analysis requires multiple perspectives.

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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, marketing, HR, and customer success. Takes PRD to fully deployed, revenue-generating product with zero human intervention. Features Task tool for subagent dispatch, parallel code review with 3 specialized reviewers, severity-based issue triage, distributed task queue with dead letter handling, automatic deployment to cloud providers, A/B testing, customer feedback loops, incident response, circuit breakers, and self-healing. Handles rate limits via distributed state checkpoints and auto-resume with exponential backoff. Requires --dangerously-skip-permissions flag.

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Orchestrates design workflows by routing work through brainstorming, multi-agent review, and execution readiness in the correct order. Prevents premature implementation, skipped validation, and unreviewed high-risk designs.

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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.

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Quantum-resistant, self-learning version control for AI agents with ReasoningBank intelligence and multi-agent coordination

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Meta-skill que orquestra todos os agentes do ecossistema. Scan automatico de skills, match por capacidades, coordenacao de workflows multi-skill e registry management.

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Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.

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AI agent development workflow for building autonomous agents, multi-agent systems, and agent orchestration with CrewAI, LangGraph, and custom agents.

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MCP Agent Mail - Mail-like coordination layer for multi-agent workflows. Identities, inbox/outbox, file reservations, contact policies, threaded messaging, pre-commit guard, Human Overseer, static exports, disaster recovery. Git+SQLite backed. Python/FastMCP.

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