anybrowse

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

No annotations provided, so description carries full burden. It discloses output format ('markdown') and operational limits ('up to 10'), but lacks critical behavioral details: error handling (partial failures?), idempotency, timeout behavior, and whether the operation is read-only or destructive.

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?

Two sentences with zero waste. First sentence front-loads functionality, constraints, and output format. Second sentence provides usage guidance. Every word earns its place with no 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?

Adequate for a simple 2-parameter tool with full schema coverage. It covers the primary use case, limitations, and sibling differentiation. Minor gap: doesn't describe what happens if some URLs in the batch fail (partial success vs. total failure) given no output schema exists to document this.

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?

With 100% schema description coverage, the baseline is 3. The description confirms the 'up to 10' constraint mentioned in the schema but doesn't add rich semantic context, examples, or format details beyond what the schema already provides for the 'urls' and 'context' parameters.

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?

Description explicitly states the core action ('Scrape multiple URLs'), quantity constraint ('up to 10'), and output format ('as markdown'). It clearly distinguishes itself from the sibling tool 'scrape' by emphasizing the batch capability.

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 explicit comparison to sibling tool: 'More efficient than calling scrape() in a loop,' guiding users toward batch operations. However, it doesn't clarify when to use this versus 'crawl' or 'extract' siblings, nor does it explicitly state when NOT to use it (e.g., for single URLs).

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, description carries full burden. It discloses output structure (title, URL, full content in Markdown) but omits operational details critical for external web operations: rate limits, failure modes (captchas/blocks), latency, or read-only safety assurance.

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?

Two tightly constructed sentences with zero waste. Front-loaded with core action (Search... and scrape), followed by return value description. Every clause earns its place.

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?

Compensates adequately for missing output schema by describing return structure (title, URL, full content). With 100% schema coverage on 3 simple parameters, description provides sufficient context for invocation despite lacking operational caveats.

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%, establishing baseline 3. Description reinforces that 'q' targets Google specifically and implies the Markdown conversion workflow, adding slight semantic value beyond schema definitions, though schema already documents parameters comprehensively.

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?

States specific action (Search Google + scrape to Markdown) and resource (top search results). Implicitly distinguishes from siblings 'scrape' (direct URL) and 'search' (likely metadata only) by describing the combined workflow, though explicit differentiation would strengthen it further.

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 implied usage through functional description (use when you need full page content from search results), but lacks explicit when-to-use guidance or contrasts with sibling tools like 'batch_scrape' or 'extract'.

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?

No annotations are provided, so the description carries full burden. While it mentions the JSON output format, it fails to disclose critical behavioral traits: whether it makes live HTTP requests, caching behavior, rate limits, error handling, or that it is read-only/safe.

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?

Well-structured and front-loaded with the core purpose. Slightly redundant in detailing the schema format and examples that are already comprehensively documented in the parameter schema, but every sentence contributes 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?

Adequately covers the tool's unique value proposition (schema-defined extraction) and use cases for a 3-parameter tool. Would benefit from describing the output structure or error behaviors given the lack of output schema and annotations, but sufficiently complete for selection.

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?

Input schema has 100% description coverage with detailed format specifications and examples. The description largely repeats this information (schema format and example) rather than adding new semantic context, meeting the baseline for fully documented schemas.

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 specific action (extract), resource (structured data from any URL), and output format (JSON). It effectively distinguishes from sibling scraping tools by emphasizing schema-based structured extraction versus raw scraping.

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 implied usage context through concrete examples (prices, availability, product details, contact info) but lacks explicit guidance on when to use this versus siblings like 'scrape' or 'crawl', or when extraction might fail.

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?

No annotations provided, so description carries full disclosure burden. It effectively communicates critical behavioral traits: 84% success rate, handling of JavaScript/Cloudflare protection, stealth/CAPTCHA bypass mechanisms, rate limits (10/day free tier), and structured output format with metadata. Strong coverage for an external API tool.

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?

Well-structured with logical progression: capabilities → output format → usage tip → rate limits. Front-loads core purpose effectively. Rate limit information (including upgrade path), while containing marketing URL, provides necessary operational constraints for the agent. No tautological waste.

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?

No output schema exists, but description adequately compensates by specifying return format ('structured markdown with title and metadata'). Covers success probability, anti-bot behaviors, and rate limiting—sufficient context for a 2-parameter scraping tool with external dependencies.

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?

Input schema has 100% description coverage, establishing baseline of 3. Description adds usage guidance for 'context' parameter ('get more relevant results'), adding semantic value beyond the schema's functional description, though minimal additional detail provided for 'url' parameter.

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?

Clear specific verb ('Convert') and resource ('URL to clean, LLM-ready Markdown'), with specific output format mentioned. Implies single-URL usage via 'any URL' phrasing, distinguishing implicitly from 'batch_scrape' sibling, though explicit comparison is missing.

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 specific usage tip for the 'context' parameter ('provide context to get more relevant results'), offering practical guidance for effective invocation. However, lacks explicit when-to-use/when-not-to-use guidance comparing against siblings like crawl, extract, or batch_scrape.

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, description carries full burden and delivers well: discloses API provider (Brave), performance traits ('fast, reliable, no rate limits'), return structure ('titles, URLs, and descriptions as structured JSON'), and scope limitation (no scraping). Could explicitly state read-only 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?

Two sentences with zero waste. Front-loaded with API identification and key traits, followed by return format and scope distinction. Every word serves a purpose.

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?

Compensates well for missing output schema by detailing JSON return structure. Mentions rate limits and provider. Sufficient for a 3-parameter search tool, though could mention result freshness or safe search defaults.

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. Description does not add parameter-specific syntax, format constraints, or examples beyond what schema documents for q, count, and context.

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?

Specific verb 'Search' with clear resource 'the web using Brave Search API'. Critically distinguishes from siblings via 'without scraping the pages', clearly differentiating it from batch_scrape, crawl, extract, and scrape tools.

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 clear context via 'without scraping the pages' which implicitly contrasts with scraping siblings. However lacks explicit 'when to use search vs when to scrape' guidance or prerequisite conditions.

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