benchmark_run

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

Without annotations, the description carries the full burden. It discloses that measurementRef must be from a raw artifact and that model self-report never sets the bar, but does not describe other behavioral traits like whether it is destructive, permissions needed, or what the outcome of recording a run entails.

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 efficient sentences with no wasted words. The first sentence states the purpose, the second adds a critical constraint. Front-loaded and to the point.

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 no output schema and no annotations, the description is adequate for the basic purpose and a key constraint, but lacks details on return values, side effects, or integration with sibling tools. It is minimally complete for an agent.

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 schema has low coverage (33%), but the description adds meaning for 'measurementRef' (recorded raw artifact) and 'arm' (baseline sets bar). This compensates for the missing schema descriptions, though 'runId' remains unexplained.

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 specific action 'Record a tool-measured run of an arm through the frozen benchmark' and distinguishes the arm 'baseline' as a special case that sets the bar. This is a specific verb+resource and differentiates from siblings like 'reverify_run' or 'initialize_loop_run'.

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 provides clear context: requires a measurementRef from a recorded raw artifact, not model self-report. While it doesn't explicitly exclude alternatives, it gives enough guidance on prerequisites and the special role of 'baseline'.

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