List AI Models

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, which are sufficient. The description adds that it returns model IDs and active status, which is useful but not critical beyond the annotations.

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 concise sentence that conveys the essential information without any fluff or unnecessary details.

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 annotations, a full input schema with descriptions, and an output schema, the description adequately covers the tool's behavior. It mentions return values (IDs and status), which is sufficient for a read-only list operation. Minor gap: no explicit mention of pagination, but that's covered by parameters.

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?

The input schema has 100% description coverage, setting a baseline of 3. The description does not add new parameter semantics beyond what the schema provides, except for the project_id parameter referencing list_projects, which is minimal.

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 clearly states the tool lists AI models tracked by Peec AI, with specific examples like ChatGPT and Perplexity. The verb 'list' and resource 'models' are unambiguous, and the tool is distinct from siblings such as list_projects or list_chats.

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 does not explicitly state when to use this tool versus alternatives like list_projects. It implicitly references the need to call list_projects to find project IDs, but lacks explicit guidance on when not to use this tool or what distinguishes it from other list tools.

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