Scrapy MCP Server

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 mentions 'advanced techniques' but doesn't explain what these entail (e.g., rate limits, authentication needs, potential for blocking, or how it handles dynamic content). For a web extraction tool with no annotations, this leaves significant gaps in understanding operational behavior and risks.

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 appropriately sized and front-loaded, starting with the core purpose. The bulleted list efficiently details extractable data types, and the final sentence clarifies the data_type parameter. There's minimal waste, though the structure could be slightly improved by integrating the data_type explanation more seamlessly.

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 (web extraction with 2 parameters), no annotations, and an output schema present, the description is partially complete. It covers the purpose and parameter semantics to some extent but lacks behavioral details and usage guidelines. The output schema likely handles return values, so that gap is mitigated, but overall completeness is limited for effective agent use.

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 description adds meaning for the 'data_type' parameter by listing its possible values (all, contact, social, etc.) and examples of what each extracts, which is valuable since schema description coverage is 0%. However, it doesn't explain the 'url' parameter beyond what the schema title implies. With 2 parameters and low schema coverage, this partial compensation results in a baseline adequate score.

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 verb 'extract' and resource 'structured data from a webpage', specifying what the tool does. It lists concrete examples of data types (contact info, social media links, etc.), making the purpose specific. However, it doesn't explicitly distinguish this tool from sibling tools like 'scrape_webpage' or 'extract_links', which might have overlapping functionality.

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 no guidance on when to use this tool versus alternatives. With sibling tools like 'scrape_webpage', 'extract_links', and 'scrape_with_stealth' available, there's no indication of scenarios where this tool is preferred, prerequisites, or exclusions. Usage is implied only through the data_type parameter, but not contextualized against other tools.

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