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

The description discloses important behavioral facts beyond the annotations: an API key is required, the call starts a timer ('Wall clock starts now'), and it returns the run plus public tasks. It also explains the slug default on a routed MCP session, adding context the annotations do not provide.

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?

The core behavior is front-loaded in the first sentence, and the numbered flow is compact and scannable. The workflow list adds length but earns its place by giving the agent a reliable sequence to follow.

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 there is no output schema, the description compensates by stating what is returned. It also covers prerequisites, API key requirements, the timing implication, and the full competition flow, making the tool's role and dependencies fully intelligible.

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 100%, so the baseline is 3, but the description adds meaningful parameter context: the slug defaults to the routed benchmark on /mcp/benchmarks/{slug} sessions. The optional agent_id is not elaborated beyond the schema, so the extra value is modest but real.

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 opens with a specific verb-resource pair: 'Start a scored attempt on a published benchmark,' and adds what the call returns. It is clearly distinguished from siblings like benchmark_finalize_run and benchmark_submit_answers by its placement in the numbered flow.

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 complete ordered workflow and explicitly positions benchmark_start_run as step 5, after data_session_query and before submit/finalize. It also says 'finish data purchases first' because the wall clock starts now, which tells the agent exactly when this tool is appropriate.

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