Statistics Denmark Table Search

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false, covering the safety profile. The description adds a concrete behavioral warning about the large response when query is omitted (2,000+ tables), which goes beyond annotations. It does not mention pagination or rate limits, but these are minor given the read-only, idempotent nature.

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 and front-loaded: it starts with the core action, lists the return fields, explains the follow-up pipeline, and ends with example keywords. Every sentence serves a purpose, and there is no fluff. It is slightly dense but appropriately sized for a search tool.

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 search tool that feeds into a multi-step pipeline, the description covers the return fields, the pipeline usage (table_info and query), and gives practical example keywords. It does not detail pagination or error handling, but given an output schema exists and the pipeline is explicit, 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 coverage is 100% and the parameter descriptions in the schema already detail both query and subjects, including example keywords and the note about omitting query to list all tables. The main description repeats the example keywords but adds no new semantic information beyond what the schema provides, so it sits at the baseline for full coverage.

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 searches or lists StatBank tables by keyword and/or subject area, lists the specific fields returned (table IDs, titles, unit, timestamp, periods, dimensions), and explicitly positions it as the entry point for the pipeline by instructing to use the returned ID with table_info and query. This distinguishes it from the sibling tools (subjects, table_info, query).

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?

It gives clear context on when to use the tool (searching tables) and directs to subsequent steps (table_info, query). It does not explicitly state when not to use it (e.g., if you already have a table ID, skip to table_info), and it does not mention the subjects tool as an alternative for scoping, but the schema description for the subjects parameter references it. The usage flow is implied strongly enough to be useful.

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