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

With no annotations, the description carries full burden. It discloses the async nature ('Returns run_id immediately. Use get_run_status to poll'), which is crucial. However, it omits other behavioral traits like resource usage, cancellability, or rate limits, making it minimally adequate for a simple launch tool.

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 extremely concise with two sentences, no fluff, and front-loads the primary action. Every word adds value, making it efficient for an AI agent to parse.

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?

For a tool with 2 parameters and no output schema, the description covers the basic workflow (launch and poll) and return value. However, it lacks explanation of the depth parameter's impact and potential long-running nature, leaving gaps for optimal usage.

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?

The description adds no information about parameters beyond the schema. Schema coverage is 50% (prompt described, depth not), and the description fails to explain the depth enum values or prompt quality guidelines. The description should compensate for low coverage but does not.

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 'Launch an AI scientific research run', with a specific verb and resource. It distinguishes itself from siblings like autosearch_get_run_status (polling) and autosearch_get_run_paper (retrieving papers), making the tool's purpose unambiguous.

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 provides clear usage context: use this tool to start a run, then poll with get_run_status. It implies when to use this tool vs alternatives but does not explicitly state when not to use it or list all sibling alternatives directly.

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