perplexity_list_models

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the action ('List all available models') but doesn't describe traits like whether it's a read-only operation, requires authentication (implied by 'perplexity_login' sibling), rate limits, or output format. For a tool with zero annotation coverage, this leaves significant behavioral gaps, scoring a 2.

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 directly states the tool's purpose without any fluff or redundancy. It's front-loaded with the core action and resource, making it highly concise and well-structured, earning a 5.

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 tool's low complexity (0 parameters, no output schema) and lack of annotations, the description is adequate but incomplete. It covers the basic purpose but misses contextual details like authentication needs (suggested by 'perplexity_login'), typical use cases, or output expectations. This is minimally viable but has clear gaps, scoring a 3.

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 tool has 0 parameters, and the input schema has 100% description coverage (though empty). The description doesn't need to add parameter semantics, as there are none to document. This meets the baseline of 4 for zero parameters, as it appropriately doesn't discuss non-existent inputs.

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 verb ('List') and resource ('all available Perplexity AI models'), making the purpose unambiguous. It distinguishes from siblings like 'perplexity_ask' (querying models) and 'perplexity_status' (checking service status), though it doesn't explicitly mention these distinctions. The description is specific but lacks explicit sibling differentiation, warranting a 4.

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 no guidance on when to use this tool versus alternatives. It doesn't mention scenarios like selecting a model for use with 'perplexity_ask', checking model availability before queries, or comparing it to 'perplexity_status' for service health. Without any usage context or exclusions, this is minimal guidance, scoring a 2.

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