execute_query_with_sampling

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

No annotations are provided, so the description must fully disclose behavioral traits. It only says a query is executed with sampling, but does not clarify if the operation is read-only or destructive, what happens on failure, or whether it affects system state. The return value (output schema) is not described, leaving significant behavioral ambiguity.

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 sentence of 7 words, which is concise but under-informative. It lacks structure or additional context. While brevity is valued, the description does not earn its place by providing sufficient detail to guide the agent effectively.

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 5 parameters, no parameter descriptions, and an output schema not elaborated, the description fails to cover key aspects such as parameter roles, return format, or edge cases. The agent is left without essential information to invoke the tool correctly, making the description incomplete for its complexity.

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 0%, meaning no parameter descriptions in the schema. The description adds no information about any of the 5 parameters (sql_query, window_size, sample_count, sample_interval, sample_all_messages) beyond their names and defaults. An agent cannot infer their meanings or usage constraints, which severely hinders correct invocation.

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) and the resource (SQL query) with the key differentiator (with proper sampling configuration). This distinguishes it from sibling 'execute_query' which likely lacks sampling, making the purpose specific and actionable.

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 implies usage for queries needing sampling ('proper sampling configuration'), but it does not explicitly state when to use this tool versus alternatives like 'execute_query' or 'restart_job_with_sampling'. No when-not-to-use guidance is provided, which is a gap for an agent deciding between similar tools.

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