run_benchmark_turn_detection

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, and it provides none. It does not say whether the benchmark is read-only, whether it is expensive/long-running, what it measures, or what happens as a result of running it.

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?

It is short, but this is under-specification rather than conciseness — a single four-word fragment that does not earn its place by conveying any actionable information. There is no front-loaded purpose statement beyond the name itself.

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 no annotations, no output schema, and no parameter documentation, the description must explain what the benchmark does and what the agent gets back; it does neither. An agent has no basis to decide when or why to invoke it.

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 tool takes zero parameters, so there is nothing for the description to clarify beyond schema; per the scoring baseline for parameterless tools, a 4 is appropriate. No parameter meaning is missing.

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 merely restates the tool name with no added specificity: it does not say what kind of benchmark, what data it runs against, or what 'turn detection' means here. It also fails to distinguish itself from siblings like analyze_turn_status or predict_semantic_closure, all of which operate in the same turn-analysis domain.

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?

There is no indication of when to use this benchmark versus the sibling diagnostic tools, nor of any prerequisites, inputs, or intended context. At best the word 'benchmark' weakly implies an evaluation/measurement scenario, but nothing is stated explicitly.

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