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

Beyond the readOnlyHint and idempotentHint annotations, the description discloses important behavioral constraints: only SELECT statements are allowed, DDL/DML and file-reading functions are rejected, and the tool operates on tables staged by oecd_query_dataset. This adds meaningful safety and restriction context beyond what annotations already convey.

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 sentences, each carrying essential information: the core operation, required precursor and use cases, and a hard environment prerequisite. There is no filler or redundant restatement of the tool name or schema.

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 a 100%-covered schema, an output schema present, and annotations already signaling read-only/idempotent behavior, the description supplies the remaining critical context: the dependency on oecd_query_dataset, the need to call oecd_dataframe_describe first, and the DuckDB provider condition. An agent has enough information to invoke this 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?

Both parameters are already fully described in the schema (100% coverage), so the baseline is 3. The description adds value by explaining that sql should reference table names from oecd_dataframe_describe and that canvas_id identifies the DataCanvas session from oecd_query_dataset, reinforcing the relationship between parameters and workflow.

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 states a specific action ('Run a read-only SQL SELECT'), names the target resource ('OECD observation tables staged on a DataCanvas by oecd_query_dataset'), and clearly separates this from sibling tools like oecd_dataframe_describe and oecd_query_dataset. It uses a concrete verb and resource, making the tool's role immediately identifiable.

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 clear usage context: call oecd_dataframe_describe first to learn table/column names, use this tool for aggregation, filtering, GROUP BY, JOIN, and window functions, and note that it is only available when CANVAS_PROVIDER_TYPE=duckdb is set. It does not explicitly enumerate when-not-to-use alternatives, but the prerequisite and environment condition provide solid operational guidance.

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