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dispatch_gemini_agent

Send coding, analysis, or research tasks to a background Antigravity subagent and get an immediate job_id, so your orchestrator keeps running without blocking.

Instructions

Dispatch a coding, analysis, or research task to a background Antigravity subagent. Returns immediately with a job_id so the orchestrator is never blocked.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
taskYesDetailed task description or prompt for the worker agent.
modelNoWhich live model to run this job on, e.g. 'Gemini 3.8 Flash (High)'. The live catalog (versions, families, and thinking-effort tiers) changes over time and depends on the connected Antigravity IDE session — call list_available_models rather than assuming a name. Defaults to the fastest available flash-tier model.
context_filesNoOptional absolute file paths to include as context for the agent.
system_instructionNoCustom system instructions for the subagent worker.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations, the description carries the full burden, and it does disclose the key behavioral trait: asynchronous, non-blocking execution that returns a job_id immediately. However, it omits the rest of the job lifecycle — that the job runs in the background and must be polled, whether it can be cancelled, failure behavior, and any auth/session prerequisites (the model param hints at dependence on the connected IDE session).

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 with zero filler. The core action is front-loaded and the non-blocking return contract is stated second, which is exactly the right ordering.

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?

There is no output schema, so the description usefully states the return value (a job_id). Combined with full parameter coverage, an agent has enough to invoke the tool. The remaining gap is the lifecycle handoff — it never points at check_agent_job or cancel_agent_job for the dispatched job.

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 all four parameters are already documented, including the pointer to list_available_models for the model param. The description adds no additional parameter meaning, so the baseline of 3 applies.

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

Purpose4/5

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

States a specific verb and resource: dispatching coding/analysis/research work to a background Antigravity subagent, and it names the async nature (returns immediately with a job_id). It does not explicitly contrast itself with siblings like gemini_code_search or check_agent_job, but the dispatch semantics are unmistakable.

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

Usage Guidelines3/5

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

Usage is implied rather than stated: 'background' and 'orchestrator is never blocked' suggest long-running work that shouldn't be awaited inline. There is no explicit when-to-use vs. gemini_code_search, and no instruction to follow up with check_agent_job or cancel_agent_job — the natural next steps are left for the agent to infer.

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