kalei_model

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

With no annotations, the description carries the burden of behavioral disclosure. It implicitly signals a read-only operation through 'Get' and describes what data is returned, which is useful. However, it does not mention error behavior, data freshness, availability, or any side effects or prerequisites.

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, efficient sentence that front-loads the action and resource, then compactly enumerates the key return fields. Every part earns its place, with no filler 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?

For a simple one-parameter get operation, the description covers the input and the main output fields despite the lack of an output schema. It is less complete on usage context and edge cases, and it does not clarify how this tool relates to kalei_profile_model, leaving some ambiguity for selection.

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 parameter's meaning and example format are already fully documented by the schema. The description adds no additional semantic information about agent_id beyond what the schema provides, which warrants the baseline score.

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 uses a specific verb ('Get'), identifies the resource ('a specific model's cognitive profile'), and enumerates the returned content (Cognum score, 10-dimension breakdown, cognitive type, volatility index). It is clear on its own, but it does not explicitly differentiate itself from the similar-looking sibling kalei_profile_model.

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?

There is no guidance on when to use this tool versus its many siblings, especially kalei_profile_model or kalei_compare. An agent is left to infer the intended use case from the description and tool name alone.

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