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

With readOnlyHint, idempotentHint, and destructiveHint already provided by annotations, the description adds value by specifying exactly which state fields are returned, including the platform's learned rhythm and failure reasons. This gives the agent expectations for the response without violating existing hints.

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 compact: two sentences plus a field list and example. The core purpose is front-loaded, the return format is presented clearly, and every sentence serves a purpose – no fluff.

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?

With only one parameter, no output schema, and full annotations for safety, this is sufficient to call the tool correctly. The description names the expected return fields, so the agent knows exactly what it will receive. Even the source of the input is covered.

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 description coverage is 0%, but the description explicitly states where valid table_ids come from and provides a JSON example. This supplies meaning beyond the bare uuid type, compensating for the schema gap.

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 states a precise verb and resource: 'One table as the builder sees it' and enumerates the specific state fields it returns (promotion, live version, refresh schedule, rhythm, last refresh, failure). This immediately distinguishes it from siblings like get_table_schema (schema) and list_tables (list), so an agent can route the call correctly.

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 gives a clear context and even advises where table_id values come from ('register_recipe, get_my_dataset or a run receipt'), which is practical input guidance. It does not explicitly list alternatives or exclusions, but the distinct set of returned fields makes it obvious when this tool is appropriate.

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