exa

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

Annotations already cover read-only, idempotent, and non-destructive behavior. The description adds useful context about returning clean markdown and metadata, and supporting batching. However, it claims 'full content' while the schema includes a maxCharacters default of 3000, and the description does not disclose that pages are truncated unless the limit is increased, which is a significant gap in behavioral transparency.

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 three short sentences, each adding value: the core function, usage guidance, and return expectation. It is front-loaded with the most important information and avoids any fluff or repetition.

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 simple read tool with two parameters and strong annotations, the description is mostly complete: it states the input (URLs), output (text and metadata), and when to use it. The only notable omission is the character limit caveat, which prevents a perfect completeness score.

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?

The schema already provides descriptions for both parameters (urls and maxCharacters), covering 100% of the parameters. The description contributes little beyond repeating the batching capability already in the schema, so it does not add meaningful extra meaning beyond the structured data.

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 reads a webpage's full content as clean markdown, with an explicit verb and resource. It also distinguishes from the sibling tool web_search_exa by specifying its use case: after search when highlights are insufficient or for reading any URL.

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 explicitly says to use this tool after web_search_exa when highlights are insufficient, and it highlights best uses (extracting full content from known URLs, batching multiple URLs). This provides clear when-to-use guidance and names the alternative, leaving no ambiguity about when to choose this tool over the sibling.

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

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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is well covered. The description adds behavioral context beyond annotations: it explains the return type ('clean text content from top search results'), provides query formulation guidance (describe the ideal page, not keywords), and mentions category filters. It doesn't describe pagination or rate limits, but the annotations cover the key behavioral traits.

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 well-structured with clear sections ('Best for', 'Returns', 'Query tips') and front-loads the core purpose. It's slightly longer than strictly necessary, but every section earns its place by providing actionable guidance. The formatting with line breaks and bullet-like structure makes it scannable.

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 search tool with no output schema, the description does a good job explaining what to expect ('clean text content from top search results') and how to use it effectively. It covers the main use cases, query formulation, category filters, and follow-up strategy. It doesn't mention result count limits or pagination, but the numResults parameter is documented in the schema. The description is complete enough for an agent to call this tool correctly.

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 three parameters thoroughly. The description adds value by reinforcing the query style ('describe the ideal page, not keywords') and explaining the category: syntax ('Use category:people / category:company to search through Linkedin profiles / companies respectively'). This goes beyond the schema's parameter descriptions, which already include similar guidance, but the description's reinforcement is useful.

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 function: 'Search the web for any topic and get clean, ready-to-use content.' It specifies the resource (web) and the action (search), and distinguishes it from the sibling web_fetch_exa by noting it returns search results and suggesting follow-up with web_fetch_exa for fetching URLs. This is a specific verb+resource pairing that an agent can easily understand.

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 explicit guidance on when to use this tool: 'Best for: Finding current information, news, facts, people, companies, or answering questions about any topic.' It also gives query tips and explicitly names the alternative: 'If highlights are insufficient, follow up with web_fetch_exa on the best URLs.' This clearly routes the agent to the right tool for the right situation.

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