dataprobe_query_sql

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

With no annotations, the description carries the full burden of behavioral disclosure. It does state 'read' indicating a non-mutating operation, but it does not disclose return format, pagination behavior, side effects, or authorization requirements. The description is too sparse to provide meaningful behavioral transparency.

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 a single, front-loaded sentence that is easy to parse. It avoids fluff and gets straight to the point. However, it is somewhat under-specified for the tool's complexity, which slightly lowers the score from a 5.

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 tool has 3 parameters, no output schema, and no annotations. The description only states the basic action, omitting critical context such as what the result looks like, whether a dataset_id is required, and how the limit applies. This is insufficient for an AI agent to fully understand the tool's behavior.

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 only 33% coverage (limit's description), and the description adds no parameter information. It does not explain what 'sql' should contain, how 'dataset_id' is used, or the meaning of 'limit' beyond schema. With low schema coverage and no description compensation, parameter semantics are effectively absent.

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's function: 'Execute a read SQL query through DataProbe.' It has a specific verb ('execute'), a clear resource ('SQL query'), and a scope ('read'), which distinguishes it from siblings like dataprobe_ask (which likely handles natural language) and dataprobe_health/list_datasets.

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?

No guidance is provided on when to use this tool versus alternatives. It does not mention any prerequisites, exclusions, or compare itself to sibling tools like dataprobe_ask. The only implicit clue is 'SQL query', but there is no explicit context for choosing it over other DataProbe tools.

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