Update an existing data spec, step 2: run analysis after uploading

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

The description goes beyond annotations by disclosing that the call waits synchronously for a terminal state ('ready' or 'failed') and may time out. It also implicitly warns against re-calling, aligning with idempotentHint=false. No contradictions with annotations.

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?

Two sentences, no fluff. The first sentence provides the purpose and the second gives timeout handling. Information is front-loaded and every word earns its place.

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 role in a multi-step workflow and the rich schema, the description is complete: it explains the prerequisite (update_data_spec), the behavior (waits for ready/failed), and the fallback (get_status). No output schema is present, but the outcome is clearly stated.

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%, with each parameter already described. The tool description adds little beyond the schema; the only slight addition is referencing that specId comes from update_data_spec, but that info is already in the schema description. Baseline 3 applies.

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 identifies the tool as step 2 of a data spec update workflow ('after uploading the file(s) returned by update_data_spec'), and states its specific action: kicks off AI analysis and waits for 'ready' or 'failed'. It also distinguishes itself from siblings by referencing the poll alternative (get_status).

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?

Explicitly says when to call ('after uploading the file(s) returned by update_data_spec') and provides a clear alternative for timeout situations ('Poll with get_status instead of re-calling this if it times out'). This is direct and actionable guidance.

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