sqlbot_ask_data

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

With no annotations, the description must disclose behavioral traits. The description only states the tool processes natural-language questions via a pipeline. It does not reveal whether the tool modifies data, authentication requirements (though parameters hint at keys), rate limits, or side effects. The finish_step parameter suggests multi-step behavior, but this is not explained.

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 (one sentence) and front-loaded with the core purpose. However, given the tool's complexity (9 parameters), it could be slightly longer to include essential context without becoming verbose.

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 is incomplete for an agent to fully understand the tool's capabilities. It does not mention the output format, the meaning of the finish_step enum, or how the access_key/secret_key are used. Given no output schema and low schema coverage, more context is needed.

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 only 44% (4 of 9 parameters have descriptions). The description adds no information about parameters, failing to compensate for the low coverage. Parameters like lang, return_img, finish_step, include_analysis, and data_preview_limit are not explained, leaving an agent without guidance on their purpose or defaults.

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 that the tool allows asking a natural-language data question via a Text-to-SQL pipeline. It uses a specific verb ('Ask') and resource ('SQLBot'), and the mention of 'existing Text-to-SQL pipeline' distinguishes it from sibling tools like sqlbot_describe_table or sqlbot_list_datasources.

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 provides no guidance on when to use this tool versus alternatives. It does not mention scenarios, prerequisites, or when not to use it. Sibling tools exist for specific tasks like describing tables or listing sources, but no comparison or context is given.

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