search_codes

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: codes are opaque integers that cannot be guessed, geography search without type_code returns the type list, and a geography search at the top-level codelist returns success with no matches. This is valuable operational transparency beyond the schema.

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 dense and every sentence earns its place. The core purpose is front-loaded, followed by essential behavioral caveats and concrete examples. It is longer than average, but the complexity of the two-step geography behavior justifies the length.

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 complexity, an output schema exists, and there is no annotation coverage, the description is complete. It covers the main use case, the tricky geography case, the fallback behavior, and example calls. An agent has enough context to invoke the tool 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?

Although schema coverage is 100%, the description adds significant semantic value: it explains the relationship between concept='geography' and type_code, shows concrete call examples, and clarifies that type_code is mandatory for geography but unnecessary for other dimensions. This goes well beyond the schema's property descriptions.

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 immediately states the tool's purpose: 'Resolve dimension values to the numeric codes fetch_data needs.' This is a specific verb plus resource and clearly distinguishes it from siblings like search_datasets and get_dataset_dimensions by explaining it produces the codes required by fetch_data.

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 when-to-use guidance: 'Always come here first.' It explains the two-step geography workflow, when type_code is needed versus omitted, and that non-geography dimensions are searched directly. This leaves little ambiguity about how to use the tool correctly.

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