dataproduct_query

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

With no annotations provided, the description carries the full burden. It transparently discloses that the tool connects to Snowflake/Databricks, executes the provided SQL, enforces data contract terms, and returns at most 100 rows. It does not explicitly clarify whether only read-only queries are allowed or describe error behavior, which prevents a perfect score.

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 concise and well-structured: a clear opening sentence, necessary governance/access context, and a straightforward Args/Returns layout. No filler or redundancy.

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?

The description covers access requirements, data contract compliance, parameter meanings, and return shape (row count and 100-row limit). Since an output schema exists, return details need not be fully repeated. It lacks explicit error conditions and read-only clarification, so it is strong but not exhaustive.

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 input schema has 0% description coverage, but the Args section fully defines every parameter, including the business-purpose requirement and the tip to use fully qualified table names. This adds substantial meaning beyond the raw schema.

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 action ('Execute an SQL query') and the target ('a data product's output port'). It also distinguishes itself from siblings like search/get/request_access by specifying that the tool runs SQL against the underlying data platform.

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 states prerequisites: access to the output port is required, and queries must comply with data contract terms. It does not explicitly name sibling tools as alternatives or specify when not to use the tool, so it stops short of a 5.

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