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

Beyond the annotations (readOnlyHint, openWorldHint), the description adds meaningful behavioral details: fetches in parallel, uses anti-detection, returns combined results with status, strategy used, and content size, and clearly marks failed URLs. This gives the agent a solid mental model of execution and output.

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 for arguments, returns, and an example. It is somewhat verbose but all content earns its place—the example is useful, and the returns section compensates for the missing output schema. Tight enough for its informative 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's moderate complexity (parallel fetching, strategy selection) and rich annotations, the description is fully self-sufficient. It provides return format, failure behavior, usage context, and an example, leaving no critical gap for an agent to invoke the 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?

The input schema already provides full descriptions for both parameters (100% coverage), including max items and enum options. The description adds an example and clarifies that URLs must include http(s):// but largely repeats what the schema states, so it does not materially enhance parameter understanding beyond the schema.

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: 'Fetch multiple URLs in parallel' with 'anti-detection capabilities.' It distinguishes itself from sibling web_fetch by emphasizing parallelism and speed, making its purpose unmistakable.

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 usage context: 'Use this after web_search to fetch the top 3-4 results in a single call instead of making separate web_fetch calls.' This directly names the alternative (web_fetch) and gives a concrete scenario, guiding the agent precisely when to choose this tool.

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?

Adds significant behavioral detail beyond annotations: rotating user agents, optional proxy, fallback to Jina Reader on blocks, and the ability to choose strategies. It also discloses the return format (HTML vs markdown) and the included status/final URL/strategy, enriching the tool's operational model.

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?

Despite being detailed, the description is well-structured with clear sections (purpose, strategies, alternative, args, returns). Each sentence contributes valuable information without redundancy, and the front-loaded core purpose makes it easy to scan.

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?

With no output schema, the description compensates by detailing return values (page content, HTTP status, final URL, strategy used). It covers tool alternatives, strategy selection, and parameter semantics thoroughly, making it self-sufficient for an agent to select and invoke successfully.

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 coverage is 100%, but the description adds extra meaning by explaining the strategies in depth (auto, direct, jina) and how they behave, including fallback logic and output format differences. This goes beyond the schema's brief parameter descriptions, enhancing the agent's understanding.

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 fetches web page contents with anti-detection capabilities, specifying the verb 'Fetch' and resource 'contents of a web page'. It distinguishes itself from sibling web_bulk_fetch by noting that the latter is for multiple URLs, making the purpose unambiguous.

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 advises using web_bulk_fetch for multiple URLs, and details when to use each strategy (e.g., 'jina' best for JS-heavy sites). The 'auto' strategy's fallback behavior is explained, providing clear when-to-use guidance.

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 this as safe (readOnly, idempotent, non-destructive), and the description adds useful context: it uses the Brave Search API, requires user's API key, and avoids IP blocks. It also describes the return format. It does not disclose rate limits or error handling, but the disclosure is adequate given the annotation coverage and search tool nature.

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: a one-sentence purpose, a brief note on the replacement behavior, a bulleted arg list, a returns section, and examples. Every section earns its place, and the content is front-loaded with the core function. No redundant filler.

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 and the absence of an output schema, the description sufficiently covers return values (title, URL, description, extras) and parameter meanings. It does not detail error scenarios or rate limits, but for a straightforward search tool with rich annotations and schema, this is almost complete.

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 input schema covers all parameters with descriptions and defaults. The description adds value by providing usage guidance, such as keeping queries to 1-6 words, explaining freshness format, and including concrete examples. This enriches the schema's raw parameter definitions.

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 using the Brave Search API' and lists the return payload (titles, URLs, descriptions, snippets). It distinguishes itself from the siblings by being a search tool rather than a fetch tool, and also explicitly differentiates from the native web_search by highlighting anti-detection capabilities.

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 explains why this tool should be used over the native web_search (anti-detection, own API key, avoiding IP blocks). It does not explicitly mention web_fetch or web_bulk_fetch as alternatives, but the search-vs-fetch distinction is implicit from the tool name and description. While clear context is provided, explicit when-not-to-use guidance for sibling tools is missing.

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