get_pi_models

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

Annotations already provide readOnlyHint, idempotentHint, and openWorldHint, indicating safe, consistent, and potentially incomplete results. The description adds no additional behavioral context (e.g., caching, authorization requirements). While it does not contradict annotations, it adds minimal value beyond them.

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?

A single sentence with no unnecessary words. It is front-loaded with the action and resource, making it easy for an agent to parse quickly.

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 tool is a simple list operation with good annotations. The description lacks details about return format (e.g., what fields are returned), but given the straightforward nature and presence of annotations, it is mostly complete. Minor gap for an agent expecting a full overview.

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?

Tool has no parameters, and input schema coverage is 100% (empty schema). The description does not need to add parameter details. Baseline 4 applies since no parameters to document.

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?

Description uses a specific verb ('List') and resource ('available Predictive Intelligence solutions'), clarifying the tool focuses on classification/similarity models. This clearly differentiates it from numerous sibling 'list_*' tools.

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 explicit guidance on when to use this tool versus alternatives. The description implies it's for listing PI models, but does not specify when not to use it or mention alternative tools for model management, which could help an agent decide.

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