anybrowse

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

With no annotations, the description carries the burden of behavioral disclosure. It adds the batch limit ('up to 10'), output format ('markdown'), and efficiency claim, but does not disclose partial failure behavior, rate limits, or authentication needs. These are meaningful gaps but the core behavior is covered.

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 two sentences, front-loaded with the primary action and includes only essential details. Every word earns its place; no redundancy or 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 simplicity (2 params, 1 required, no output schema), the description adequately covers purpose, batch limit, and output format. It does not detail result structure or error handling, which would improve completeness, but the core usage context is sufficiently clear.

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 describes both parameters (urls and context) with clear descriptions. The tool description adds 'up to 10' which duplicates the schema, and 'markdown' which is output-related, not parameter-specific. Since schema coverage is 100%, the description adds minimal extra parameter meaning, aligning with the baseline of 3.

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: 'Scrape multiple URLs at once (up to 10) and get all results as markdown.' It uses a specific verb and resource, and distinguishes itself from the sibling 'scrape' tool by referencing a batch operation and efficiency over a loop.

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 clear context for use ('Scrape multiple URLs at once') and explicitly mentions the alternative ('More efficient than calling scrape() in a loop'), implying when to choose this over individual scraping. It lacks an explicit when-not-to-use caveat, but the alternative is clearly named.

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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It does disclose the main behavior (Google search, scraping top results, converting to Markdown) and the output structure. However, it lacks caveats such as potential scraping failures (e.g., blocked pages), rate limits, or truncation of 'full page content.' The claim 'full page content' may be optimistic and is not qualified.

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 two sentences, both front-loaded with the main verb and resource. It avoids redundancy and includes essential output information. Every sentence earns its place, making it highly concise and well-structured.

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 that there is no output schema, the description adequately covers return values (title, URL, full page content). It also conveys the core workflow. However, it could be more complete by mentioning the effect of the 'count' parameter on the number of results or any limitations, though the schema handles parameter details. Overall, it is fairly complete for a straightforward tool.

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 (q, count, context). The description adds no additional semantic meaning beyond what the schema provides; it merely restates the general purpose. Thus, the 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 uses a specific verb-resource pair: 'Search Google for a query and scrape the top results to Markdown.' It clearly distinguishes from siblings by combining search and scraping into one operation, and explicitly states the return structure (title, URL, full page content). This is a precise and unambiguous statement of purpose.

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 implies its use case (search + scrape to Markdown) but provides no explicit guidance on when to choose this tool over alternatives like 'search' (which might only return links) or 'scrape' (which might target a specific URL). No exclusions or alternatives are mentioned, making it only 'implied usage' rather than explicit 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?

With no annotations, the description carries the burden of disclosure. It covers the core behavior (schema-driven extraction to JSON) but does not mention potential error cases, response shape beyond 'JSON', or any limitations (e.g., URL restrictions). This is adequate but not rich.

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 sentences, front-loaded with the purpose, and every sentence earns its place: purpose, schema format, and use cases. No wasted words or redundancy.

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 tool with no output schema, the description should clarify the output shape. It says 'as JSON' but does not explicitly state that the response is a JSON object with the requested fields. However, this is easily inferred from the schema input, and the description is otherwise complete for a simple extraction tool.

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%, so the baseline is 3. The description adds a simple example and clarifies the 'Provide a schema' requirement, but it does not significantly expand on the schema's own descriptions or explain the 'context' parameter beyond what's already in 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 a specific verb and resource: 'Extract structured data from any URL as JSON'. It differentiates from siblings by emphasizing schema-driven field extraction, which is distinct from batch_scrape, crawl, scrape, and search.

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?

It provides clear context with 'Great for prices, availability, product details, contact info' and implies when to use it (when you know the fields you want). However, it does not explicitly mention when not to use it or name alternative tools, so it falls short of a full 5.

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?

With no annotations, the description carries full behavioral disclosure. It explicitly mentions JavaScript rendering, dynamic content handling, stealth mode/CAPTCHA bypass, an 84% success rate, and the return format (Markdown with title/metadata). This is transparent about both capabilities and limitations.

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 front-loaded with the main purpose, followed by capabilities, return format, a tip, and pricing. Each sentence contributes distinct information, though the pricing/upgrade details are less critical for an AI agent invoking the tool.

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?

The description covers the tool's purpose, capabilities, return format, and a usage tip. It lacks explicit differentiation from sibling tools and a detailed breakdown of the Markdown output structure, but for a 2-parameter tool without an output schema, it is largely sufficient.

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 baseline is 3. The description adds value by advising to provide 'context' for more relevant results, enriching the context parameter beyond its schema description. The URL parameter is clear from the schema already.

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 'Convert any URL to clean, LLM-ready Markdown,' which is a specific verb+resource statement. It clearly distinguishes this tool from siblings like batch_scrape (multiple URLs) and extract (structured data) by focusing on single-page conversion to Markdown.

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?

Provides a tip to supply 'context' for better results, which is a usage guideline. However, it does not explicitly state when to use scrap over batch_scrape, crawl, extract, or search, leaving the choice implied rather than prescribed.

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?

With no annotations, the description carries the full burden. It discloses the underlying API (Brave), the output format (structured JSON), and that it does not scrape pages. It also makes a specific claim about 'no rate limits,' which is useful behavioral context. However, it omits potential error cases or pagination details.

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 a single, well-structured sentence that front-loads the core purpose and adds only useful details (source, speed, reliability, output format, no scraping). Every phrase earns its place with zero redundancy.

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 only three parameters and no output schema, the description is sufficiently complete. It states the return fields (titles, URLs, descriptions) and the format (structured JSON), which is enough for an agent to understand what to expect. The tool is simple enough that no further context is needed.

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%, so the baseline is 3. The description does not add any parameter-specific meaning beyond what is already in the schema. The 'context' parameter is described in the schema, not the description, so no extra value is provided.

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 'Search the web using Brave Search API' with a specific verb and resource. It explicitly mentions what it returns (titles, URLs, descriptions) and differentiates from sibling scraping tools by adding 'without scraping the pages.'

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 implies when to use it by distinguishing from scraping tools ('without scraping the pages'), which serves as an exclusion. However, it does not explicitly name sibling alternatives like scrape or extract, nor does it provide a clear when-not-to-use scenario.

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