search_web

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions that results include 'optional AI-enhanced HTML, markdown content, and structured data,' which adds some context about output features. However, it fails to disclose critical behavioral traits such as rate limits, authentication needs, costs (implied by 'costs 1 credit' in the schema but not in the description), or error handling. For a search tool with 10 parameters, this is insufficient.

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 front-loaded, consisting of two sentences that directly state the tool's purpose and key output features. There's no wasted verbiage, and it efficiently communicates the core functionality. A slight deduction is made because it could integrate cost or sibling tool context more seamlessly.

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 (10 parameters, no annotations, no output schema), the description is moderately complete. It covers the basic purpose and output formats but lacks details on behavioral aspects, usage guidelines, and output structure. Without annotations or an output schema, the agent must infer much from the input schema alone, leaving gaps in understanding the tool's full 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 fully documents all 10 parameters. The description adds minimal value beyond the schema by hinting at 'AI-enhanced' outputs and 'structured data,' but it doesn't elaborate on parameter interactions or provide additional semantic context. This meets the baseline of 3 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 clearly states the tool's purpose: 'Search the web using Crawleo's AI-powered search engine.' It specifies the verb ('Search') and resource ('the web'), and mentions the engine's AI-powered nature. However, it doesn't explicitly differentiate from its sibling tool 'crawl_web' (e.g., by contrasting search vs. crawl operations), which prevents a perfect score.

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 no guidance on when to use this tool versus its sibling 'crawl_web' or other alternatives. It lacks context about appropriate scenarios, exclusions, or prerequisites (e.g., when to prefer search over crawl). This leaves the agent without usage direction beyond the basic purpose.

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