fleet_bench

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

The description discloses that the benchmark runs in the background, returns a job_id, and that the finished job contains a report with recommendations. This adds useful behavioral context beyond the schema. However, with no annotations, it does not address potential side effects, idempotency, or whether it modifies configuration. It is adequate but not comprehensive.

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 description is a single, focused sentence that front-loads the core action ('Start the self-learning benchmark in the background') before adding details. It avoids redundancy and each clause adds value.

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?

The description covers the main purpose, async behavior, and output (job_id/report). However, it omits prerequisites (e.g., whether fleet_setup must be run first), does not explain the 'mode' parameter, and the phrase 'every node/model' is potentially contradictory with the optional 'nodes' and 'models' parameters. Given 6 parameters and no output schema, more detail would improve completeness.

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 description adds context for categories, nodes, models, and optional probes, but does not explain the 'mode' parameter (quick/full) or elaborate on 'explore' beyond its schema description. With only 33% schema coverage, the description partially compensates but leaves key parameters like mode ambiguous. It provides some added meaning but not complete.

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 a specific action: 'Start the self-learning benchmark in the background' with details about graded coding tasks and optional resource probes. It distinguishes from siblings by focusing on starting a benchmark, unlike fleet_status (status) or fleet_setup (configuration). The scope is unambiguous.

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?

No explicit guidance on when to use this tool vs alternatives. It does not mention any exclusions, prerequisites, or direct comparison to sibling tools like fleet_delegate or fleet_job. The implied use case is 'when you want to run a benchmark', but this is not stated.

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