webclaw

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

With no annotations provided, the description carries the full transparency burden. It successfully discloses the automatic fallback to 'webclaw cloud API when bot protection is detected,' which is substantive behavioral context. However, it omits rate limits, auth requirements, and output format 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?

Three tightly constructed sentences: purpose declaration, input guidance, and fallback behavior. Every sentence earns its place with 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?

With 9 sibling tools sharing similar domains ('scrape', 'crawl', 'summarize'), the description lacks explicit differentiation to aid tool selection. While the core functionality is covered, the absence of output schema disclosure and sibling comparisons leaves gaps for agent decision-making.

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 a baseline of 3. The description adds value by clarifying the relationship between 'schema' and 'prompt' parameters ('either... or'), indicating they are alternative specification methods—a semantic constraint not explicit in the schema alone.

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 ('Extract') and resource ('structured data from a web page') are clear, plus method ('using an LLM'). However, it does not explicitly differentiate from siblings like 'scrape' (raw HTML) or 'crawl' (multiple pages), only implying the distinction via the LLM mention.

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?

Implies usage by stating input options ('Provide either a JSON schema or a natural language prompt'), but lacks explicit when-to-use guidance versus alternatives like 'scrape' or 'summarize', and does not state prerequisites or exclusions.

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