query

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It discloses that multi-turn conversations are supported via sessionId and that the response includes rich metadata (citations, sources, images, related questions). It does not mention side effects or require explicit safety notes, but the query nature implies a read operation.

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 concise (3 sentences), front-loaded with the primary action, and each sentence adds value: purpose, specialization, multi-turn feature, and return metadata. There is no redundancy or unnecessary detail.

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 description is largely complete for a query tool: it explains what it does, what makes it special, and what it returns. It does not cover edge cases, error handling, or rate limits, and there is no output schema, but the rich metadata mention helps. Overall, it provides sufficient context for an AI agent to use it correctly.

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 schema already documents all parameters thoroughly. The description does not add parameter-specific meaning beyond the schema; it only mentions sessionId for multi-turn in general terms, which is already covered. Thus, a baseline of 3 is appropriate.

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 queries Perplexity AI with a prompt and specifies that it is specialized for web search with citations and related questions. While it does not explicitly differentiate from sibling tools like search or fetch, the purpose is unambiguous.

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 clear context on when to use this tool: for web searches with citations, sources, and related questions, and for multi-turn conversations. However, it does not mention when not to use it or explicitly compare to alternatives like search or fetch.

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