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

Annotations show readOnlyHint=false and destructiveHint=false, so no contradiction. The description adds that API key is required, that answers can be JSON objects for the json_fields grader, and that finalization requires a completed data purchase. It doesn't disclose idempotency or partial-failure behavior, but it adds useful context beyond the annotations.

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?

Three sentences, all informative: purpose, answer format, next step. No filler. The first sentence establishes the primary action and requirement; the ending routes to the next tool. Minor deduction for not front-loading the parameter semantics before the pipeline note.

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 submit tool with no output schema, the description covers the core action, prerequisites (API key), accepted answer formats, return value (accepted count), and next step. It doesn't detail error cases, validation rules, or whether answers replace existing ones, but those are less critical given the pipeline context is clear.

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 only 33%, but the description compensates by explaining answer content (scalar or JSON object for json_fields grader), and the schema itself documents run_id, answers, and agent_id. The description adds meaning to the 'answers' parameter (formats accepted, grader-specific detail) beyond what the schema provides.

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 clearly states the verb ('submit'), the resource ('answers for an in-progress benchmark run'), and key details about answer formats (scalar or JSON object). It also names the next step (benchmark_finalize_run), which distinguishes this from siblings like benchmark_start_run and benchmark_get_results.

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 states API key requirement and explicitly instructs calling benchmark_finalize_run next, which gives clear usage context. It doesn't explicitly say when not to use it or name alternatives for different scenarios, but the sibling names make the pipeline position clear.

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