dax_benchmark

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

With no annotations provided, the description fully carries the burden of behavioral disclosure. It honestly discloses the optional engine cache clearing, the number of runs, the return values (coldMs, warmMs[], rowCount), and that timings are client wall-clock per run including full row drain. It also explicitly states what is measured, making the tool's behavior highly transparent.

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 efficiently front-loaded with the purpose, and every sentence carries useful information. It is slightly longer than strictly necessary, but the additional details about measurement methodology and tool pairing justify the length without being 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?

Given the tool's moderate complexity and absence of an output schema, the description is remarkably complete. It covers the workflow, return values, side effects (cache clearing), and provides guidance on complementary tools. No critical aspects are missing for an agent to select and invoke the tool correctly.

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 coverage is 75% (3 of 4 parameters documented). The description adds meaning by explaining the number of runs ('run the query N times') and the optional cache clearing, and it also describes the return structure which indirectly clarifies parameter effects. Although sessionId is not elaborated in the description, the schema plus the overall workflow provide adequate context, exceeding the baseline.

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 states the tool benchmarks a DAX query, a specific verb+resource, and clearly distinguishes it from siblings like start_dax_trace/stop_dax_trace and run_dax. It also specifies the output format and optional cache clearing, leaving no ambiguity about its function.

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 clear context by explaining the benchmarking workflow and explicitly recommends pairing with start_dax_trace/stop_dax_trace for deeper FE/SE split analysis. It does not explicitly state when not to use this tool or exclude alternatives, but the complementary usage is clearly indicated.

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