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swarm_task

Decompose a high-level goal into parallel sub-tasks executed by autonomous agents, then synthesize outputs into a single deliverable.

Instructions

Auto-decompose a high-level goal into N parallel sub-tasks, fan out agents across all of them, then run a synthesis agent that produces one unified deliverable. Returns immediately with swarm_id and sub_job_ids. Use get_swarm_status to poll progress.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
goalYesHigh-level goal to decompose and execute across parallel agents
repo_urlYesGitHub repo URL for all sub-agents and the synthesis agent
max_agentsNoMaximum number of parallel sub-agents (default 10, hard cap 50)
agent_modelNoModel override for all spawned agents (optional)
agent_driverNoDriver for all spawned agents (optional, default: claude)
synthesis_outputNoPath in the repo where the synthesis agent writes its deliverable (default: swarm-synthesis.md)
synthesis_promptNoCustom instruction for the synthesis agent. Defaults to: review all outputs and write a unified deliverable.
max_budget_per_agentNoMax USD budget per agent (sub-agents and synthesis). Default 5.
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description carries full burden. Describes the process (decomposition, parallel execution, synthesis) and return values. Lacks details on side effects, error handling, or authorization needs, which would improve transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with no wasted words. First sentence covers the core workflow, second tells what is returned and next steps. Well front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 8 parameters and no output schema, description adequately explains the overall process, return values, and polling. Could mention expected output format or error scenarios, but sufficient for an AI agent to understand usage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3. Description adds no new semantics beyond schema descriptions for parameters like goal or synthesis_prompt. It mentions the synthesis agent writes to a path, but that is covered in schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states verb 'auto-decompose' and resource 'high-level goal'. Distinguishes from siblings like spawn_agent by describing parallel decomposition and synthesis. Mentions immediate return of swarm_id and sub_job_ids.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly tells when to use (decomposing high-level goals) and points to get_swarm_status for polling. Does not explicitly mention when not to use or alternatives, but context with siblings implies distinction.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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