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Invoke agent

invoke_agent

Send a message to an agent and receive the assistant's reply, or get a run ID for polling. If the agent requires human input, it returns an awaiting status to continue with input prompts.

Instructions

Send a message to an agent and, by default, wait for the turn to finish and return the assistant's reply. Running an agent spends credits. If the run pauses on a human-input request it returns status "awaiting_input" (use list_pending_inputs + answer_pending_input). Pass wait=false to return a run_id immediately and poll get_run_result.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
waitNoWait for the turn to complete and return the reply (default true). If false, returns a run_id to poll.
messageYesThe message to send to the agent.
agent_idYesThe agent's UUID.
session_idNoOptional thread/session id to continue an existing conversation; omit to start a new one.
Behavior4/5

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

Beyond annotations (openWorldHint, destructiveHint=false), the description discloses credit consumption, waiting behavior, and human-input pauses. Lacks details on error handling but covers key behavioral traits.

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?

Three sentences, all essential. Front-loaded with main action, then credits, then alternative flows. No redundant information.

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?

Covers main use cases, human-input, and polling. References sibling tools. No output schema, but not required. Adequate for an agent to use the tool correctly.

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

Parameters4/5

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

Schema coverage is 100%, and the description adds meaning: wait explains its impact, session_id is clarified as optional for continuing conversations, agent_id is UUID, message is self-explanatory. Good added context.

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 clearly states the tool's purpose: sending a message to an agent and waiting for a reply. It distinguishes from siblings by mentioning human-input handling and polling alternatives.

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?

The description provides explicit when-to-use guidance, including when to use wait=false and the need to switch to list_pending_inputs/answer_pending_input for human-input cases. References sibling tools.

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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