
Multi-Agent Orchestrator
The hard part of multi-agent work isn't spawning agents — it's deciding what deserves parallelism, what each agent needs to not duplicate work, and how failures cascade
- Map parallel vs serial task dependencies
- Define per-agent context and output contracts
- Design failure fallback and verification steps
$12.99
· or 65 creditsSecure checkout via Stripe
Included in download
- Map parallel vs serial task dependencies
- Define per-agent context and output contracts
- Ready for Claude Code
Sample input
I need to build a system that audits high-volume legal docs using Claude. How should I structure the agents for speed and accuracy?
Sample output
Structure: Parallelize 'Extraction' across 5 agents. Use a sequential 'Conflict Checker' agent to merge. Add a 'Senior Auditor' agent for final verification. Output Contract: JSON per doc. Topology: Fan-out/Fan-in.
The hard part of multi-agent work isn't spawning agents — it's deciding what deserves parallelism, what each agent needs to not duplicate work, and how failures cascade
$12.99
· or 65 creditsSecure checkout via Stripe
Included in download
- Map parallel vs serial task dependencies
- Define per-agent context and output contracts
- Ready for Claude Code
- Instant install
Sample input
I need to build a system that audits high-volume legal docs using Claude. How should I structure the agents for speed and accuracy?
Sample output
Structure: Parallelize 'Extraction' across 5 agents. Use a sequential 'Conflict Checker' agent to merge. Add a 'Senior Auditor' agent for final verification. Output Contract: JSON per doc. Topology: Fan-out/Fan-in.
About This Skill
The hard part of multi-agent work isn't spawning agents — it's deciding what deserves parallelism, what each agent needs to not duplicate work, and how failures cascade when one agent in a pipeline returns bad output. This skill designs the full orchestration: which tasks benefit from parallelism vs. which are serial dependencies, what context each subagent needs and nothing more, how results are validated before being handed downstream, and where human checkpoints belong. It maps your workflow into an agent graph with clear boundaries, failure modes, and fallback strategies — before you write a single tool call. Use it when you're building multi-step Claude pipelines, Claude Code subagent flows, or any system where one model's output feeds another. Give it your goal, your available tools, and your constraints; it returns an architecture you can implement without discovering the coordination problems at runtime.
Use Cases
- Map parallel vs serial task dependencies
- Define per-agent context and output contracts
- Design failure fallback and verification steps
- Select optimal agent team topologies
Known Limitations
- Does not write deployment code
- Not for single-agent tasks
- Logic based on architectural patterns, not runtime execution monitoring.
How to Install
mkdir -p ~/.claude/skills && curl -sL https://www.agensi.io/api/install/multi-agent-orchestrator -o /tmp/multi-agent-orchestrator.zip && unzip -o /tmp/multi-agent-orchestrator.zip -d ~/.claude/skills && rm /tmp/multi-agent-orchestrator.zipFree skills install directly. Paid skills require purchase - use the download button above after buying.
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Claude Code, API, framework-based agents
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