run_task_and_wait

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

With no annotations provided, the description discloses important behaviors: auto-polling, default timeout (10 minutes), polling interval (5 seconds), and automatic syncing to persistent storage. It does not cover failure behavior or error handling, but the provided details are substantial.

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

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

The description is three sentences long, efficiently conveying purpose, behavior, and defaults. It is front-loaded with the main action. Minor improvements could be made by combining related information, but it is already concise.

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

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

Given the tool's moderate complexity and the existence of an output schema, the description covers the core workflow, polling behavior, and persistence. It lacks details on timeout handling or task failure, but overall it is sufficiently complete for an agent to use effectively.

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

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

Schema coverage is 100%, so the description does not need to add much. It repeats default values for timeout and poll_interval already in the schema, adding minimal extra semantics. Baseline score of 3 is appropriate.

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

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

The description clearly states the tool's action: 'Submit an AI application task and wait for completion (auto-polling)'. It explains that it 'Combines submit_task + query_task_outputs into a full workflow', which distinguishes it from sibling tools like submit_task and query_task_outputs.

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

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

The description implies when to use this tool (as a full workflow combining submission and polling) but does not explicitly state when not to use it or mention alternatives. The context is clear enough for an AI agent to infer appropriate usage.

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