search_web_quick

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

No annotations are supplied, so the description carries the full burden. It usefully discloses real-time latency, per-call cost (0.002 USDC), and that returned URLs are 'verified', and the operation is a non-destructive read. It omits rate limits, whether the auth_token_or_tx parameter is required for a paid call, and any failure behavior, which a no-annotation mutation-capable service should ideally state.

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?

Content is front-loaded: purpose, cost, then a compact 'Usage Guidelines' block. Every sentence carries information, though framing two short lines as 'Usage Guidelines' is slightly padded and could be a single clause.

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?

An output schema exists, so return fields need not be spelled out, and the description stays appropriately brief on that front. Yet with zero annotations, the description leaves gaps around authentication (the optional x402 token), pricing verification, and how this tool relates to the deep-research siblings, so an agent must still guess at the invocation context.

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 query, max_results, and auth_token_or_tx. The description adds no syntax, format, or constraint detail beyond the schema, only the cost and the shape of results. Baseline 3 applies when the schema does the heavy lifting.

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 states a specific verb and resource: 'fast real-time keyword web search' returning titles, links, and snippets, plus a cost figure. This is far more concrete than a tautology. However, it does not distinguish itself by name from siblings like deep_research_topic or oracle_grounding, leaving the agent to infer the boundary from the word 'quick' alone.

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 line 'designed specifically for LLM autonomous agent retrieval' describes a general audience but gives no when/when-not conditions and names no in-toolset alternative (Tavily and s.jina.ai are external competitors, not routing targets). Usage is implied by 'fast' and 'keyword' contrasting with deeper research tools, but it is never made explicit.

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