find_jobs

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

With no annotations, the description carries the full burden for behavioral disclosure. It goes beyond a simple statement by revealing that invalid status values return the valid list rather than an empty result—a non-obvious failure mode—and that dates use ISO format. The inlined next appointment also hints at the return structure. This is substantial added context.

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 concise sentences each add unique value: purpose and a key feature, date format, and an exclusion with an alternative. The information is front-loaded and there is no fluff or redundancy.

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 the presence of an output schema, the description is not required to explain return values. It covers purpose, date format, an important edge case, and an explicit alternative. For a 5-parameter tool with no annotations, it could further clarify filters like customer_id or pagination, but the existing guidance is sufficiently robust for an agent to avoid major pitfalls.

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 0%, so the description must compensate, but it only partially does. It clarifies date format for since/until and mentions status behavior, but leaves customer_id and limit semantically implicit. The parameter names are self-explanatory, yet the description could do more to define filtering semantics.

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 ('List jobs') and a distinguishing feature ('with the next appointment inlined'), making the tool's purpose immediately clear. It also explicitly differentiates from the sibling tool find_customer, reducing ambiguity about scope.

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 provides a clear when-not case: 'Not for finding a customer — use find_customer.' This directs the agent away from a likely misuse. It also notes a behavioral edge case (invalid status returns a valid list) that affects usage, though it does not enumerate all sibling distinctions (e.g., job_detail).

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