company_evals

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

The description hints at a side effect with 'optionally learn the errors into memory', but it does not explicitly state whether the tool reads, writes, modifies, or deletes data, nor does it disclose permissions, reversibility, or other behavioral characteristics. This is a significant gap given the absence of 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?

The description is a single, compact sentence with no redundant fluff. It efficiently conveys the core actions in two clauses, though the dense phrasing slightly hurts readability.

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 lacks essential contextual details: no explanation of the output schema, no parameter semantics, no examples, and no indication of expected input format. Given the tool's apparent complexity (evaluation logic, memory learning), the description is severely incomplete for an agent to use it correctly.

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?

None of the five parameters (now, learn, project_id, bundle_json, records_json) are explained in the description. The schema provides only names and types, and with 0% description coverage, an agent has no meaningful understanding of how to populate this tool's inputs.

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 two main actions: scoring recorded recommendations against closed periods and scoring the simulator against standard scenarios, plus an optional learning step. However, terms like 'brief digest', 'decided option', and 'standard scenarios' are vague, leaving the exact purpose somewhat unclear.

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 guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, context, or conditions that would help an agent decide to invoke it.

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