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

The description goes well beyond the annotations by disclosing the extreme latency and response size ('a two-sentence question measured 192 seconds and returned 86 KB after 10 upstream searches'), the timeout risk ('Many clients time out well before it answers'), and the flat pricing. It also warns against looping, which is critical behavioral context for an agent deciding whether to call this 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 dense but every sentence earns its place: the core purpose, the required model, the output shape, the performance warning with concrete numbers, and the routing guidance. The warning is front-loaded after the purpose, and the sibling comparison closes it efficiently.

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?

For a complex, slow, report-generating tool with an output schema and full parameter documentation, the description covers everything an agent needs: what it returns, how long it takes, when to use it, and when not to. The output schema handles return-value details, so nothing critical is missing.

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 13 parameters. The description adds the required model value ('sonar-deep-research') and names the output fields, but it doesn't add new meaning to individual parameters beyond what the schema provides. Baseline 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 opens with a specific verb and resource ('Commission a report: this endpoint runs many searches and writes a long, cited document'), which clearly distinguishes it from the other Perplexity endpoints. It also names the required model and the key output fields, so an agent can tell this is the deep-research report generator among the sibling tools.

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 gives explicit when-to-use guidance: 'call it only when a report is genuinely the deliverable, and never in a loop.' It also contrasts with the sibling endpoints ('For anything you would read in one sitting, the other three Perplexity endpoints answer in seconds'), which is exactly the kind of alternative routing an agent needs.

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