「orchestration」の検索結果

Comprehensive AI/ML development guide for LangChain, LangGraph, and ML model integration in FastAPI. Use when building LLM applications, agents, RAG systems, sentiment analysis, aspect-based analysis, chain orchestration, prompt engineering, vector stores, embeddings, or integrating ML models with FastAPI endpoints. Covers LangChain patterns, LangGraph state machines, model deployment, API integration, streaming, error handling, and best practices.

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Build production-ready AI agents with Microsoft Foundry and Agent Framework. Use when creating AI agents, selecting LLM models, implementing agent orchestration, adding tracing/observability, or evaluating agent quality. Covers agent architecture, model selection, multi-agent workflows, and production deployment.

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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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Dynamic agent composition and management system. USE WHEN user says create custom agents, spin up custom agents, specialized agents, OR asks for agent personalities, available traits, agent voices. Handles custom agent creation, personality assignment, voice mapping, and parallel agent orchestration.

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Provides the "how-to" for workflow / task execution orchestration. Defines methods for planning multi-phase task/workflows, implementing them through agent delegation, and managing artifacts.

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AgentHero AI - Hierarchical multi-agent orchestration system with PM coordination, file-based state management, and interactive menu interface. Use when managing complex multi-agent workflows, coordinating parallel sub-agents, or organizing large project tasks with multiple specialists. All created agents use aghero- prefix.

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Design and implement agentic AI workflows and patterns. Covers ReAct, planning agents, tool use, memory systems, and multi-agent orchestration. Use when building autonomous AI agents, implementing complex task automation, or designing intelligent workflow systems.

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Conduct multi-agent task orchestration and workflow coordination.

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Coordinate multiple AI agents and skills for complex workflows

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Expert agent organizer specializing in multi-agent orchestration, team assembly, and workflow optimization. Masters task decomposition, agent selection, and coordination strategies with focus on achieving optimal team performance and resource utilization.

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Multi-agent task orchestration for Claude Code. When given multiple tasks to execute, use this skill to spawn parallel worker agents through Sibyl's MetaOrchestrator instead of Claude Code's built-in Task tool. This enables true multi-process execution with budget controls, quality gates, and coordination.

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This skill should be used when the model's ROLE_TYPE is orchestrator and needs to delegate tasks to specialist sub-agents. Provides scientific delegation framework ensuring world-building context (WHERE, WHAT, WHY) while preserving agent autonomy in implementation decisions (HOW). Use when planning task delegation, structuring sub-agent prompts, or coordinating multi-agent workflows.

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Create and manage Databricks Agent Bricks: Knowledge Assistants (KA) for document Q&A, Genie Spaces for SQL exploration, and Multi-Agent Supervisors (MAS) for multi-agent orchestration. Use when building conversational AI applications on Databricks.

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Open protocol for AI agent interoperability enabling standardized communication between agents, applications, and humans across different frameworks

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Expert agent organizer specializing in multi-agent orchestration, team assembly, and workflow optimization. Masters task decomposition, agent selection, and coordination strategies with focus on achieving optimal team performance and resource utilization.

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Backward-compat alias for @horizon (this skill was renamed from `pm` to `Horizon` on 2026-07-05). USE THIS only when invoked directly as `/pm` or via an existing `@pm` delegation reference — it redirects immediately to @horizon, the strategic owner of the VNX future-state layer (roadmap -> tracks -> deliverables) and the plan-first gate. Prefer `@horizon` / `vnx horizon` for anything new; this alias exists only for transition safety.

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SQLite database expertise for migrations, multi-tenant patterns, transactional safety, FTS5 virtual tables, and schema evolution. Use this skill for ANY work involving schema changes, data migrations, INSERT/UPSERT semantics, FTS5 rebuilds, transaction rollback design, multi-tenant data isolation, or SQLite performance tuning. Triggers include: writing migration SQL, modifying `_import_table`-style importers, designing UNIQUE/PK constraints, adding indexes for JOINs, debugging "rows missing" / "wrong count" / "stuck for hours" symptoms in SQLite-backed systems.

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Strategic owner of Horizon, the VNX future-state layer (roadmap -> tracks -> deliverables) and the plan-first gate. USE THIS when the user wants to plan the next VNX feature, decide what to build next, add something to the roadmap, prioritize or schedule (inplannen) work into now/next/later horizons, break a feature into deliverables, set the routing FLOOR, or run the plan-gate on a feature. The tracks DB (`vnx horizon`, alias `vnx objective`) is the source of truth; the repo ROADMAP.yaml is a generic example, not the SSOT. Plans and gates only: never dispatches, never closes open-items. The heavy multi-model plan-gate panel runs only on an explicit plan-gate step. (Renamed from `pm` 2026-07-05 — `/pm`/`@pm` still resolve via the backward-compat alias in `.claude/skills/pm/SKILL.md`.)

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Test engineer ensuring quality through unit, integration, and E2E testing strategies

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VNX feature-execution kickoff preflight. USE THIS when starting or resuming a feature or track from its plan: checking worktree/queue/staging health, finding the first promoteable dispatch, and handing off to @t0-orchestrator. Reads the feature's track + plan doc from Horizon's tracks DB (`vnx horizon`, alias `vnx objective`); the repo FEATURE_PLAN.md/PR_QUEUE.md are generic examples, not the source.

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Multi-provider deliberation panel for COMPLEX, multi-view questions — architecture, strategy, market research, and codebase sweeps. Runs a 4-stage deliberation across the provider fleet (diverge → contrarian red-team → adversarial verify → cited synthesis), the same multi-perspective rigour the plan-gate already applies to plan reviews, generalised to arbitrary questions. Use when one model's answer isn't enough and you want convergence THROUGH disagreement + verification, not a single opinion.

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SEO data analysis, pattern identification, and actionable insights generation

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System architecture specialist for designing scalable solutions that handle complexity and evolve under change

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Planning specialist that breaks a VNX feature or track into small, independently-shippable PRs with dependencies and per-PR task-class routing. USE THIS when the user wants to break a feature down into PRs, sequence the work, or turn a plan into a PR queue. Delegated to by @horizon (formerly @pm — @pm still resolves via alias). Works from Horizon's tracks DB (`vnx horizon`, alias `vnx objective`); the repo FEATURE_PLAN.md is a generated generic example, not the source.

日本語の概要は準備中です。原文の説明を表示しています。