Evaluate models against a versioned role pack

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

With no annotations provided, the description carries full behavioral burden, and it delivers: it discloses deterministic evaluators, fatal safety criteria, the evidence considered, the 2-3 offer output, the explicit 'hires nobody' safeguard, and the $0 cost of local models. This is unusually transparent for a tool definition.

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 with no filler: the first states the core action, the second summarizes evidence and output guarantees, and the third covers the local-model option. Key constraints are front-loaded and every sentence earns its place.

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 tool's outcome ('returns 2-3 offers but hires nobody'), evidence dimensions, safety criteria, and local evaluation mode, which is sufficient given the rich schema. It does not detail the exact offer structure or how offers/autonomy interact, but no output schema exists and the description still provides a solid mental model.

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 88%, so the baseline is 3; the description mainly reinforces include_local and local_only semantics rather than adding new parameter meaning. It adds the useful note that local models cost $0, but that is also present in the schema.

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 and resource: 'Run repeated, role-specific cases against 1-4 candidate models.' It also differentiates from likely siblings by stating it 'returns 2-3 offers but hires nobody,' making its evaluation-only role clear against recruit or audition.

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 establishes when this tool is appropriate—evaluating multiple models with deterministic evaluators and evidence—and gives concrete guidance for the local-model path with include_local or local_only. It does not explicitly name sibling alternatives or exclusions, but the context is clear enough for an agent to select it.

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