search

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 effectively describes key traits: the search mechanism ('via Perplexity AI with automatic model selection'), output format ('returns cited sources with summaries'), and input constraints ('uses only the query text'). However, it lacks details on rate limits, authentication needs, or error handling, which are common for such tools.

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 appropriately sized and front-loaded, with every sentence earning its place. It starts with the core functionality, adds key features, and ends with usage guidelines, all in a concise and structured manner 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 the tool's complexity (a search tool with behavioral nuances) and no output schema, the description is mostly complete. It covers purpose, usage, and key behaviors, but could benefit from mentioning response format details or potential limitations. However, it compensates well with clear guidelines and transparency.

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 both parameters thoroughly. The description does not add meaning beyond what the schema provides for parameters; it focuses on overall tool behavior instead. Baseline 3 is appropriate as the schema handles parameter documentation adequately.

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's purpose with specific verbs ('web search via Perplexity AI') and resources ('returns cited sources with summaries'). It distinguishes itself from potential siblings by specifying 'automatic model selection' and 'uses only the query text (not conversation history)', making its scope explicit and differentiated.

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 explicit usage guidelines with 'Best for: current events, factual research, technical documentation, comparative analysis.' This clearly indicates when to use this tool versus alternatives, offering specific contexts and exclusions (e.g., not for conversational history-based queries).

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