pplx_query

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

No annotations provided; description adds detail on cost (1 PRO SEARCH QUERY per call), model-specific thinking mode support, and source focus options. It doesn't cover error handling or conversation_id behavior, but otherwise is transparent.

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 efficiently structured: a brief intro, a critical cost/usage note, then a bullet-like Args section. Every sentence adds value without redundancy.

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?

With 5 parameters and an output schema (not needing return description), the description covers most aspects: purpose, cost, usage context, all parameters except conversation_id. It is sufficiently complete for an agent to use effectively.

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 0%, so description compensates by explaining query, model with enums, thinking mode availability per model, and source_focus options. However, conversation_id parameter is not described, leaving a gap.

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 'Query Perplexity AI with explicit model selection' and distinguishes from sibling pplx_smart_query by specifying when to use each.

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?

Explicitly says 'Prefer pplx_smart_query for automatic quota-aware routing. Use this only when you need a specific model or thinking mode.' Also mentions cost, providing clear when-to-use and when-not-to-use guidance.

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