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Orchestrating Multi Agent Systems Skill for Claude

Execute orchestrate multi-agent systems with handoffs, routing, and workflows across AI providers. Use when building complex AI systems requiring agent collaboration, task delegation, or workflow coordination. Trigger with phrases like "create multi-agent system", "orchestrate agents", or "coordinate agent workflows". '

1.4k tokens
context cost
SKILL.md, read when the skill is used
13
files
ships runnable scripts
0
copies elsewhere
how many repositories repackaged it
2 679
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/jeremylongshore/tons-of-skills-marketplace --skill orchestrating-multi-agent-systems

What comes with it

38 897 bytes besides the instruction
assets/README.md
assets/agent_template.ts
assets/example_coordinator.ts
assets/example_workflow.json
references/README.md
references/errors.md
references/examples.md
references/implementation.md
scripts/README.md
scripts/agent_setup.py
scripts/dependency_installer.py
scripts/env_setup.py

What it tells the agent to use

found in the instruction text
Bash runs shell commands — read the instruction before connecting
Read reads your files

The instruction itself

8 sections, as written by the author

Orchestrating Multi-Agent Systems

Overview

Design and implement multi-agent systems using AI SDK v5 with structured handoffs, intelligent routing, and coordinated workflows across AI providers. This skill covers agent role definition, tool scoping, inter-agent delegation via handoff rules, and workflow orchestration patterns including coordinator-worker and supervisor topologies.

Prerequisites

  • Node.js 18+ and TypeScript 5.0+ runtime
  • AI SDK v5 (npm install ai @ai-sdk/openai @ai-sdk/anthropic @ai-sdk/google)
  • API keys for target providers set in environment variables (OPENAI_API_KEY, ANTHROPIC_API_KEY, GOOGLE_GENERATIVE_AI_API_KEY)
  • Zod for input/output schema validation (npm install zod)
  • Familiarity with agent-based architecture patterns (coordinator, pipeline, broadcast)

Instructions

  • Initialize a TypeScript project with tsconfig.json targeting ES2022 and moduleResolution bundler
  • Install AI SDK v5 core and provider packages for each model backend required
  • Define agent roles by creating separate modules per agent, each with a system prompt, model binding, and scoped tool set
  • Implement tool functions using ai.tool() with Zod input/output schemas for type-safe execution
  • Configure handoff rules using ai.handoff() to delegate tasks between agents with clear trigger conditions and context passing
  • Build routing logic that classifies incoming requests by topic or intent and dispatches to the appropriate specialist agent
  • Wire agents into a workflow using sequential, parallel, or conditional orchestration patterns
  • Add state management to persist context across multi-step workflows using a shared context object or external store
  • Implement circuit breakers and timeout guards to prevent workflow deadlocks

10. Test each agent in isolation, then validate end-to-end handoff chains with representative inputs

See ${CLAUDE_SKILL_DIR}/references/implementation.md for the detailed implementation guide.

Output

  • TypeScript agent modules with AI SDK v5 provider bindings and system prompts
  • Tool definitions with Zod-validated input/output schemas
  • Handoff configuration mapping agent-to-agent delegation triggers
  • Workflow orchestration files defining sequential, parallel, and conditional execution paths
  • Routing classifier that maps user intents to specialist agents
  • Integration test suite covering handoff chains and fallback paths

Error Handling

| Error | Cause | Solution |

|-------|-------|----------|

| Provider configuration invalid | Missing or malformed API key in environment | Verify process.env.*_API_KEY values; check provider SDK version compatibility |

| Circular handoff detected | Agent A hands off to B which hands back to A | Implement handoff depth counter; set maxHandoffDepth and add a fallback terminal agent |

| Task routed to no agent | Routing classifier returned no match for input | Add a default catch-all route; improve classifier training data or keyword coverage |

| Tool access violation | Agent invoked a tool outside its scoped permission set | Review tools array per agent; ensure tool names match registered definitions exactly |

| Workflow timeout | Multi-step workflow exceeded deadline without completion | Set per-step timeouts with AbortController; add workflow-level deadline and partial-result handling |

See ${CLAUDE_SKILL_DIR}/references/errors.md for the full error reference.

Examples

Scenario 1: Customer Support Triage -- A coordinator agent classifies incoming tickets as billing, technical, or general. Billing queries hand off to a specialist agent with access to Stripe tools. Technical queries route to a code-analysis agent with filesystem read tools. Resolution rate target: 85% automated within 3 handoff steps.

Scenario 2: Research Pipeline -- A sequential workflow chains a web-search agent, a summarization agent, and a report-writer agent. Each agent produces structured JSON output consumed by the next. The pipeline processes 50 research queries per batch with a p95 latency under 30 seconds per query.

Scenario 3: Code Review Multi-Agent -- A supervisor agent distributes pull request diffs to specialized reviewers (security, performance, style). Each reviewer returns findings with severity scores. The supervisor aggregates results into a unified review with prioritized action items.

See ${CLAUDE_SKILL_DIR}/references/examples.md for additional examples.

Resources

  • AI SDK v5 Documentation -- agent creation, tool definitions, handoffs
  • Zod Schema Library -- input/output validation for tools and flows
  • Provider integration guides: OpenAI, Anthropic, Google Gemini
  • Coordinator-worker and supervisor orchestration pattern references
  • OpenTelemetry tracing for multi-agent observability

How to use it

Copy the folder

Take jeremylongshore/orchestrating-multi-agent-systems from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.

Install what it needs

The instructions reference npm. Without those the skill loads but fails at the first command.