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

No annotations are provided, so the description carries the full burden. It discloses key behaviors: matching includes option labels (e.g., 'rent' finds 'Rents' in CPI), collapsed Census tables with familyGeographies, and that results are confirmed to serve data (not from documentation). It could mention pagination or sorting, but the provided details are valuable and go beyond a simple statement.

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 concise but rich, with a clear flow: what it searches (topics, geography, frequency), how it matches (including options), a special behavior (collapsing geographies), a guarantee (confirmed data), and a routing suggestion. Each sentence adds value, and the key purpose is front-loaded.

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 has an output schema, the description doesn't need to explain return format. It covers the main search dimensions, edge cases (option labels, family geographies), and sets expectations (results are confirmed). With 4 optional parameters and an output schema, the description is sufficiently complete for an agent to call it correctly.

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 75%, and the remaining gaps are covered by the description to some extent. The description elaborates on the query parameter (searching across various fields) and the geography filter (for family geographies). It doesn't detail frequency semantics beyond the schema's enum, but the schema already provides that. The description adds meaningful context for query and geography, so it helps compensate for the uncovered 25%.

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 purpose: finding ABS statistical tables by topic, geography, or frequency. It specifies the resources (dataflows/tables) and differentiates it from siblings like search_options and describe_table by mentioning 'matches table names, topics and dimension names, and also option labels inside dimensions' and suggesting 'Start here, then describe_table.'

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 explicit guidance on when to use this tool: 'Start here, then describe_table.' It also explains a behavior that helps filtering: 'Census tables published at several geography levels are collapsed to one result with familyGeographies listing the others (use the geography filter to pick one).' This provides clear context for usage, though it doesn't explicitly mention when not to use it, but the context is strong.

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