perplexity_ask

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 mentions 'real-time web search' and 'synthesized from multiple online sources,' which adds some context about data sources and synthesis. However, it lacks details on rate limits, authentication needs, response format, or potential side effects, which are important for a tool performing external queries.

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 front-loaded and efficient, using two concise sentences that directly convey the tool's purpose and output. Every sentence earns its place by specifying the action, resource, and result without 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 no annotations and no output schema, the description is moderately complete for a query tool. It covers the basic purpose and data sources but lacks details on behavioral traits like error handling, response structure, or operational constraints. This leaves gaps in understanding how to effectively invoke and interpret results.

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%, with clear descriptions for both parameters (query and model). The description adds no additional parameter semantics beyond what the schema provides, such as query formatting tips or model selection guidance. Baseline 3 is appropriate since the schema does the heavy lifting.

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 specific action ('Ask Perplexity AI a question with real-time web search') and resource ('Perplexity AI'), distinguishing it from siblings like perplexity_list_models (listing models), perplexity_login (authentication), and perplexity_status (status checking). It specifies the verb+resource+scope combination precisely.

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 usage context ('Ask Perplexity AI a question with real-time web search'), suggesting this tool is for querying with web search capabilities. However, it doesn't explicitly state when to use this vs. alternatives (e.g., if other tools exist for non-search queries) or provide exclusions, leaving some ambiguity about optimal use cases.

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