get_native_query

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

With no annotations, the description carries the burden. It states the key behavior of not executing the query, but lacks details on output format, authentication requirements, side effects, or error handling. The non-execution trait is well highlighted.

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 two sentences, front-loaded with the core action, and includes a useful clarification (non-execution) and a practical use case. Every sentence adds value with no wasted words.

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?

For a tool with one parameter, no output schema, and no annotations, the description covers the basic purpose and a key behavioral trait. However, it lacks information about the return format, potential errors, or prerequisites, which would be helpful for a complete understanding.

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% for the top-level parameter 'input', though the nested 'query' property has a description. The tool description adds the context that it takes an MBQL query, but does not elaborate on the structure. Given low schema coverage, the description provides necessary but minimal added meaning.

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 converts MBQL queries to native SQL without executing, using specific verbs ('convert', 'inspect', 'debug') and identifies the resource (MBQL query to native SQL). It distinguishes from execution-focused siblings like execute_query.

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 mentions use cases ('inspecting... debugging') but does not explicitly state when not to use it or compare to alternatives like other conversion or execution tools. The context is implied but not fully specified.

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