Advanced Reasoning

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

Annotations already declare readOnlyHint=true and destructiveHint=false, indicating a safe read operation. The description adds useful behavioral context beyond annotations, such as the reasoning model ('Sonar Reasoning Pro model'), the step-by-step nature of the analysis, and the presence of numbered citations in the output. These details help the agent anticipate response style and value. However, it doesn't explicitly mention potential latency or token usage, which could be relevant for a reasoning-heavy tool.

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 and well-structured, with four sentences covering purpose, usage cases, output features, and alternatives. It is front-loaded with the core function and uses no filler. Every sentence adds valuable information, making the description efficient and easy to parse.

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 (5 params, output schema, annotations), the description is complete: it covers what the tool does, when to use it, when not to use it, and what to expect in the response. The output schema exists, so return values need not be described. The combination of annotations, schema, and description provides a comprehensive picture.

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 all 5 parameters thoroughly documented in the schema. The description mentions 'Supports filtering by recency (hour/day/week/month/year), domain restrictions, and search context size,' which echoes schema properties without adding new semantic depth. It does not explain parameter interactions or provide extra context beyond the schema, so a baseline score 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's function: 'Analyze a question using step-by-step reasoning with web grounding (Sonar Reasoning Pro model).' It distinguishes itself from siblings by specifying its niche: 'Best for: math, logic, comparisons, complex arguments, and tasks requiring chain-of-thought.' It also notes the return format: 'Returns a reasoned response with numbered citations.' This is a specific verb+resource+scope with clear differentiation.

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 guidance, stating 'For quick factual questions, use perplexity_ask instead. For comprehensive multi-source research, use perplexity_research instead.' It also lists ideal use cases ('Best for: math, logic, comparisons...'), giving the agent clear criteria for when to choose this tool over alternatives.

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