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dispatch

Send a task to a specific specialist agent, choosing backend, model, branch, and context. Use when precise agent selection matters over auto-routing.

Instructions

Send a task to one specialist. Prefer chat_send for natural language so the orchestrator auto-routes (including round-table debate). Cursor local backends can edit files only inside the write allowlist.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cwdNoWorkspace path for local Cursor agents. Must be inside an allowed directory (see list_agents writePolicy).
taskYesWhat the specialist should do
waitNoWait for completion (default true). If false, poll with get_run
modelNoPer-run model override
branchNoBranch or starting ref
pr_urlNoPull request URL for triage/review
backendNoOverride backend id from config, e.g. cursor-local, anthropic, openai, openrouter, gemini, late-infer
repo_urlNoGit remote URL for Cursor cloud agents
specialistYesSpecialist id, e.g. planner, builder, reviewer, pr-triage, or a custom external agent id
extra_contextNoAdditional context to include in the prompt
cloud_auto_create_prNoCloud Cursor agents only: open a PR when done

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.1.5
    • changedInput schema / properties / backend / description
      Previous value: -"Override backend id from config, e.g. cursor-local, anthropic, openai, openrouter, gemini, vllm-local"New value: +"Override backend id from config, e.g. cursor-local, anthropic, openai, openrouter, gemini, late-infer"
  2. First observedv0.1.0

TDQS

A4.1/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does disclose an important behavior: Cursor local backends can edit files only inside the write allowlist. However, it does not describe run lifecycle, asynchronous behavior, return values, or potential side effects like PR creation, which are relevant for a dispatch/mutation tool.

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 tight sentences: the first states purpose, the second provides routing guidance and a key constraint. No filler or repetition of schema content.

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

Completeness3/5

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

The tool is complex with 11 parameters, no annotations, and no output schema, so the description should supply more operational context. It covers purpose, routing, and one constraint, but omits what the agent can expect back from dispatch, when to poll, and how run results are surfaced. The wait and get_run schema hints help, but the description itself leaves those gaps.

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 description coverage is 100%, so the parameter list is already well-documented. The description adds minimal parameter-level meaning, mostly referencing the write allowlist constraint that affects cwd but not adding much beyond the 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?

The description opens with a specific verb and object: 'Send a task to one specialist.' This clearly distinguishes dispatch from chat_send and run_workflow by emphasizing single-specialist task routing.

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

Usage Guidelines5/5

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

It explicitly tells the agent to prefer chat_send for natural language because the orchestrator auto-routes, including round-table debate. It also adds a crucial constraint about Cursor local backends and the write allowlist, guiding when dispatch is appropriate.

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