「orchestration」の検索結果

Parallel Agent Orchestration

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。

Orchestrates multi-agent forensic investigations on public GitHub repositories, coordinating parallel evidence collection, hypothesis formation, verification, and report generation.

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。

Codex-only team orchestration: run a named team of cooperating Codex workers with durable, script-managed state. MUST USE when the user asks Codex to create, run, coordinate, inspect, archive, or delete a team of agents/threads/sessions, or to work on something as a team in parallel. FIRST inspects the active tool surface (checking tool_search for deferred tools) and tells the user the route: native MultiAgentV2 agents (flat spawn_agent with task_name) when available, Codex App threads as the fallback, or a plain-subagent split when neither set exists. The main session is always the leader; members are defined by a concrete part, ownership area, or perspective - never a vague job role; a bundled cross-platform script writes the .omo/teams state plus an auto-generated member field manual. Use a team when the work is not perfectly isolated but parallelizing helps; use plain subagents when scope is perfectly isolated or the goal is ambiguous. Triggers: team mode, teammode, make a team, run as a team, team of agents, coordinate threads, parallel Codex threads, archive the team.

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Multiagent AI system for scientific research assistance that automates research workflows from data analysis to publication. This skill should be used when generating research ideas from datasets, developing research methodologies, executing computational experiments, performing literature searches, or generating publication-ready papers in LaTeX format. Supports end-to-end research pipelines with customizable agent orchestration.

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。

Domain routing and boundary guidance for authorized container and orchestration security testing, including Docker escape, Kubernetes privilege escalation, image vulnerabilities, and service mesh bypasses. Use when a task belongs to the container testing domain and needs scope, evidence, pivot, or exit criteria.

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。

Autonomous multi-project orchestration engine. Audits all registered projects, structures work into dependency-wired tasks, dispatches parallel agents (subagents or Agent Teams), audits completions, and ships PRs. Registry-driven — works for any user with a configured project registry.

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。

Use when operating PAIDF Curation and Retrieval or NVIDIA Cosmos Curator pipelines (split, filter, caption, embed, dedup, shard, image annotate) or PAIDF Data Mining nearest-neighbor matching on Curator embeddings. Activate for Make or CLI pipeline config, GPU run preflight, FFmpeg sidecar, SAM3 keys, or Curator-to-TAO handoff. Do not use for generic ETL, vector-database RAG, model training, orchestration, or embeddings outside Cosmos Curator and PAIDF Data Mining.

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。

Select one route and return one adaptive one-to-four-workgroup bundle candidate as reply-only evidence.

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。

[omh] Tailoring enabled OMH families: turning one OMH capability family on or off so an install can be tailored instead of taken whole. Use when the user says: capability-toggle, capability policy, disable memory, enable memory, disable coding orchestration, disable a capability family, enable a capability family, 메모리 기능 꺼줘.

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。

Azure Resource Manager SDK for Durable Task Scheduler in .NET. Use for MANAGEMENT PLANE operations: creating/managing Durable Task Schedulers, Task Hubs, and retention policies via Azure Resource Manager. Triggers: "Durable Task Scheduler", "create scheduler", "task hub", "DurableTaskSchedulerResource", "provision Durable Task", "orchestration scheduler".

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。

Azure AI Projects SDK for .NET. High-level client for Azure AI Foundry projects including agents, connections, datasets, deployments, evaluations, and indexes. Use for AI Foundry project management, versioned agents, and orchestration. Triggers: "AI Projects", "AIProjectClient", "Foundry project", "versioned agents", "evaluations", "datasets", "connections", "deployments .NET".

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。

Decompose large-scale changes into independent units and spawn parallel agents in isolated worktrees. Use for migrations, refactors, codemods, and any change touching 10+ files with the same pattern.

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。

Complete AI coding workflow system. Orchestration patterns, 18 hook events, 8 agents, cross-agent support, reference guides, and searchable learnings. Works with Claude Code, Cursor, and 32+ agents.

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。

Deploy an event-driven workflow that routes S3 uploads to either Lambda or Fargate via Step Functions based on file size. Uses EventBridge to trigger a Step Functions state machine when objects are uploaded to S3. Small files are processed by Lambda, large files by a Fargate task. Includes VPC, ECR repository, ECS cluster, and scoped IAM roles. Trigger keywords: Step Functions, Fargate, Lambda, S3 event, EventBridge, ECS, ECR, file processing, workflow orchestration, serverless.

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。

Routes serverless requests to a compute form factor and the skill that owns it. Applies first to Lambda, API Gateway, EventBridge, Step Functions and event-driven work while the compute, orchestration or integration choice is open — API backends, webhooks, jobs, cron, queue/stream consumers, durable workflows, event routing, Step Functions vs Durable Functions, and Pipes vs native event source mappings for queues and streams. Decides Event Functions on-demand vs Managed Instances, Web Functions, MicroVMs, EventBridge rules/Scheduler/Pipes/bus, HTTP vs REST API. Owns shared Lambda references (cold starts, SnapStart, concurrency, event sources, function URLs, throttling, troubleshooting). Defers to the specialized skill once a request commits to one form factor or service, or describes its defining feature, even unnamed (durable checkpointing and automatic step retries, Firecracker sandbox, managed instances, Node.js server). Not for EC2, ECS/EKS/Fargate or Amplify hosting.

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。

Configures CI/CD pipelines using AWS CodePipeline, CodeBuild, CodeDeploy, CodeConnections, and CodeArtifact. Covers CodePipeline V2 (triggers, variables, execution modes, cross-account), buildspec.yml (caching, VPC, Docker), CodeDeploy strategies (blue/green, canary, linear), CodeArtifact (private package registries, auth tokens, cross-account), and source connections (GitHub, GitLab, Bitbucket). Applies when CodePipeline, CodeBuild, CodeDeploy, CodeConnections, CodeArtifact, buildspec.yml, appspec.yml, or CI/CD pipeline orchestration is referenced. Does NOT cover: ECS Fargate services or task definitions (use aws-containers), CDK Pipelines or cdk deploy (use aws-cdk), sam deploy (use aws-serverless), Amplify deployments (use aws-amplify), or GitHub Actions/GitLab CI.

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。

Notion-as-source-of-truth dispatch board for running your work like an AI agency. One Tasks database is the source of truth; tasks flow Suggestion through Discussion, To-Do, In Progress, and Done with subtasks, recurring cadences, dependencies, and template subtrees. Batch execution fans approved To-Do rows out to parallel agents with per-task model selection. Use when capturing chat to Notion, running the To-Do queue, suggesting, approving, or discussing tasks, or coordinating multi-task batches. Trigger with "/agency-os" subcommands or natural-language variants ("add a suggestion: …", "let's discuss X", "run the queue").

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。

End-to-end orchestrated workflow that runs a task the way Fable ran sessions - parallel evidence subagents, one committed plan, surgical execution with an intent gate, adversarial verification agents, honest outcome-first report. Use for non-trivial multi-step tasks when the user says "/fable-loop", "run the fable loop", or "do this the way Fable would". For the rules alone without orchestration, use fable-method; for large multi-phase projects, prefer the GSD workflow and use this inside phases.

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。

dstack is an open-source control plane for GPU provisioning and orchestration across GPU clouds, Kubernetes, and on-prem clusters.

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。

Builds and operates data pipelines — ingestion, transformation, orchestration, quality testing, and reliability of data delivery. Use this to design or debug a pipeline, decide batch versus streaming, add data quality checks, handle late or duplicate data, or work out why a dashboard's numbers changed without anyone changing the dashboard.

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。

Orchestrate workflows across multiple applications and APIs — inter-app coordination, data handoff, and multi-system task completion.

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。

Autonomous research engineering — web search orchestration, source synthesis, hypothesis formation, and structured research report generation.

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。

CrewAI multi-agent orchestration setup for collaborative AI systems

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。

Multi-agent swarm formation and coordinated execution with topology-aware agent deployment, consensus protocols, and anti-drift enforcement.

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。