GoAI Moat Web Scrape

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only says it crawls and returns Markdown; it does not mention whether the operation is read-only, whether the crawl is scoped to the starting domain, whether it follows external links, or whether rate limits or robots.txt are respected. For a tool that can request many pages, this is a significant transparency gap.

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, efficient sentence with no filler words, and it front-loads the core action and output. It could add sibling routing or behavioral caveats, but those are content gaps rather than conciseness failures.

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?

Although an output schema exists and parameters are fully documented, the tool's risk profile and selection context are underexplained. A crawler can traverse many pages, so the absence of scope boundaries, safety behavior, and guidance for when to choose this over scrape_url leaves the description incomplete for an agent trying to invoke it 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 coverage is 100%, so the schema already documents both url and limit adequately. The description adds no parameter-specific meaning beyond the schema, which matches 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 names a specific verb ('crawl'), a resource ('a website'), and the deliverable ('clean Markdown for each page'), which is clear and concrete. However, it does not explicitly differentiate itself from the sibling tool scrape_url, so an agent must infer the multi-page vs single-page distinction.

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 gives no guidance on when to use crawl_website versus scrape_url, nor does it mention any exclusions or prerequisites. The only signal is the name and sibling list, which is not enough to route an agent confidently. 'Crawl' implies whole-site coverage while 'scrape' might imply single-page, but this is left implicit.

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?

There are no annotations, so the description carries the full behavioral burden. It only promises Markdown output and does not disclose handling of dynamic content, authentication, rate limits, failure behavior, or whether the operation is read-only.

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 front-loaded sentence with no filler. It communicates the action, target, and output format efficiently.

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 one-parameter tool with an output schema, the core input and output are adequately stated. However, the lack of usage guidance and behavioral caveats means an agent is not fully equipped to handle edge cases or select between this and crawl_website.

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% and the single 'url' parameter is already described with an example. The description adds no additional parameter semantics beyond what the schema provides, so the baseline score of 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 states a specific verb ('scrape'), a resource ('a URL'), and a concrete output ('clean, LLM-ready Markdown'). It is clear and distinct enough from the sibling 'crawl_website' by emphasizing a single URL, though it does not explicitly call out the difference.

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?

No guidance is given about when to use scrape_url versus crawl_website, nor are there any exclusions or conditions. The intended use is only implied by the phrase 'scrape a URL,' leaving the agent to infer selection criteria.

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