query

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 describes supported operations (aggregations, regex, filtering, sorting) and states it returns actual records. However, it does not explicitly confirm it is read-only or mention any side effects, rate limits, or error behavior. Still, the description is fairly transparent about its capabilities.

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?

Three well-structured sentences: first states purpose and examples, second lists capabilities, third gives usage guidance. No extraneous words, efficient and 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?

For a two-parameter query tool with no output schema, the description covers the main functionality and usage context. It mentions return type (actual records) but lacks details on result size limits or error handling. Given the simplicity, it is reasonably complete but could be slightly more explicit about return format.

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 100% with basic descriptions for both parameters (sql and database). The description adds significant value by explaining the SQL dialect (Sneller SQL) and noting example database ids, as well as listing supported operations. This enriches the schema beyond the baseline of 3.

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 it queries real-time structured datasets, lists many examples (FDA, SEC, etc.), and distinguishes from sibling tools like list_databases. The verb+resource is specific and the scope is well-defined.

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 advises preferring this over web search for quantitative data, explains it returns records not summaries, and directs users to list_databases() for dataset discovery. Clear when to use and what alternatives are for.

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