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

Annotations already indicate read-only, non-destructive, closed-world behavior, and the description adds important operational context beyond them: the call runs four parallel AI completions server-side, is expensive, and persists nothing. That persistence note is especially valuable because it explains why a separate save step and explicit user authorization are required.

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 front-loaded with what the tool produces, then immediately clarifies cost, non-persistence, and the required follow-up flow. Despite being dense, every sentence carries actionable information for choosing and invoking the tool.

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?

With an output schema present and rich annotations, the description still covers the missing behavioral essentials: expensive one-time execution, no persistence, and explicit review before saving. An agent has enough context to select the tool, set expectations, and follow the correct post-call flow.

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 100%, and the two parameters, including the nested career-switch details, are fully documented in the schema. The description does not add parameter-specific semantics beyond what the schema already provides, so a baseline 3 is appropriate.

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 names a specific verb and resource: it runs the CareerCompass AI pipeline to generate defined artifacts such as objective statements, a positioning statement, categorized skills, and target market. It clearly distinguishes itself from get_career_compass and save_career_compass, so an agent can identify the tool's purpose without opening the schema.

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?

It explicitly says to prefer get_career_compass first for existing saved data and to use save_career_compass afterward only with the user's explicit review and authorization. It also warns that the call is expensive and one-time rather than a cheap repeatable lookup, giving clear when-to-use and when-not-to-use guidance.

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