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

Despite readOnlyHint and idempotentHint annotations, the description adds real behavioral value: it explains DuckDB's type inference, the numeric-comparison benefit, the CANVAS_PROVIDER_TYPE=duckdb requirement, and the fact that this is a local table query over spilled data. This goes well beyond what annotations communicate.

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?

Four sentences, each carrying distinct value: purpose, type behavior, environment prerequisite, and schema-discovery pointer. No filler or repeated schema information.

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 an output schema present and a fully documented input schema, the description covers the essential operational context: what kind of SQL is allowed, how to find table names, the environment prerequisite, and the type-inference behavior. Nothing critical is missing for an agent to invoke this 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?

The schema already covers all three parameters at 100% coverage, so the baseline is 3. The description adds meaningful semantic context for the sql parameter by explaining type coercion behavior with concrete examples (year > 2020, amount < 500), which helps an agent write effective queries.

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 opens with a specific verb and resource: "Run SELECT-only SQL against a DataCanvas table." It also distinguishes itself from socrata_query_dataset by noting the table is populated by that tool, making the query-layer role clear to an agent.

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: use this after socrata_query_dataset has populated a table, use socrata_dataframe_describe to inspect registered tables, and only use it when CANVAS_PROVIDER_TYPE=duckdb is set. It does not explicitly contrast with every sibling alternative, but the workflow guidance is strong.

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