Deep Research

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

Annotations already indicate readOnlyHint=true and destructiveHint=false, but description adds behavioral context: 'Significantly slower than other tools (30+ seconds)' and 'Returns a detailed response with numbered citations', which are not in annotations. No contradiction.

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?

Three sentences with no fluff: first defines purpose, second lists best use cases, third addresses speed and output format. Each sentence adds value.

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 has 3 parameters, output schema, and annotations, the description covers purpose, usage context, behavioral trait (slowness), and output format. No gaps.

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 parameters are fully documented in schema. Description does not add parameter-specific meaning, which is acceptable given high coverage.

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?

Description clearly states the tool conducts deep multi-source research, cites literature reviews and comprehensive overviews as use cases, and distinguishes from sibling tools by contrasting with perplexity_ask and perplexity_reason.

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 provides when to use (literature reviews, comprehensive overviews, investigative queries needing many sources) and when not to use (quick factual questions → perplexity_ask; logical analysis → perplexity_reason), with sibling tool names.

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