submit_benchmark

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

With no annotations, the description carries the full burden, and it discloses privacy behavior directly: exactly what data leaves the machine and what does not (no user IDs, no event log, no product name). It does not cover submission side effects, failure modes, or response behavior, keeping it below 5.

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?

Purpose and the opt-in constraint are front-loaded, and the enum listings for industry and stage earn their place since the schema lacks them. The trailing enum block is slightly crammed but not wasteful.

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 an opt-in submission tool with no output schema and no annotations, the privacy disclosure and enum values are good, but the meaning/format of csv_path and value_event is never explained, leaving an agent guessing about required inputs.

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 0%, so the description must compensate. It supplies the only enum values for industry and stage and gives consent usage guidance, which is real value. However, the two required params csv_path and value_event are entirely undefined, leaving half the parameters undocumented.

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 a specific verb and resource ('Submit five aggregate numbers to the anonymous benchmark') and enumerates exactly which metrics are submitted, which is unusually concrete. It does not explicitly distinguish itself from siblings like compare_benchmark, so it stops short of a 5.

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?

It clearly frames the tool as opt-in and gives an explicit precondition for consent=True ('only after the user has explicitly agreed'). It does not name alternative tools or state when-not to use it, so it lacks the exclusion/alternative coverage of a 5.

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