skill.benchmark

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

With no annotations, the description carries the full behavioral burden. It does disclose an auth requirement (MODELBOUND_API_KEY), which is genuine value, but says nothing about runtime cost, duration, side effects, or whether any data is modified — the operations surrounding it (test, optimize) suggest those questions matter.

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?

Two short sentences with no waste, and the core purpose is front-loaded ahead of the prerequisite. Appropriate size for the information conveyed.

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?

No output schema and no annotations mean the description must convey return behavior and effects, and it does not. For a benchmark tool the agent has no idea what results it produces, how long it runs, or what the single parameter must contain.

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%, so skill_id is entirely undocumented in structured fields. The description's phrase 'for a skill' only weakly implies that skill_id identifies the target skill; it adds no format, ID-source, or constraint detail.

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?

States a specific verb and resource: 'Run benchmark latency suite for a skill.' An agent can grasp the operation without opening the schema. It does not, however, distinguish it from siblings like skill.test or optimization.run, which could look similar.

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 gives a prerequisite ('Requires MODELBOUND_API_KEY') but no guidance on when to choose this over skill.test, optimization.run, or other evaluation tools. There are no exclusions or scenarios described.

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