get_operator_similarity

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

Annotations only declare readOnlyHint=true, so the description carries the burden of explaining behavior. It adds meaningful detail: percentile-rank normalization, Euclidean distance across 5 canonical metrics, computation from raw measurements, and the explicit warning that it does not perform personality matching. This goes well beyond the read-only annotation without contradicting it.

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 three short sentences with no filler. The core purpose and method are front-loaded, the data source is clarified, and the crucial 'NOT personality matching' disambiguation is included without 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?

With an output schema present, return-value details are covered elsewhere. The description provides enough context for an agent to understand methodology, data source, and outcome scope. There is no explicit guidance on when to choose this over compare_operator_to_reference or get_cohort_distribution, but the core operational context is sufficient.

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%, so the schema already documents both parameters. The description does not add meaningful parameter-level detail beyond what the schema provides, making the baseline 3 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 states a specific function: 'Nearest-neighbor operator search' with a defined methodology and output ('Returns comparable operators/cohorts'). It also distinguishes itself from what it is not ('NOT personality matching'), which differentiates it from sibling tools like get_operator_profile or compare_operator_to_reference.

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 implies when to use this tool: when you need nearest-neighbor or similarity-based operator comparisons. It gives an explicit exclusion ('NOT personality matching') but does not name alternative tools or provide direct when-to-use versus when-not-to-use guidance beyond that single exclusion.

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