extract_crawl

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

With no annotations provided, the description fully informs about behavioral traits: independent page processing, failure handling (no abort), billing only for successful pages, timing (5-15 seconds per page), page limits (default 5, max 50), warnings for >20 pages, and pre-flight requirements. It also notes the absence of js_render and explains model context sizes.

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 well-structured and front-loaded with the core purpose. It uses bullet points and clear sections. While slightly verbose, every sentence adds value. Minor improvement could be to shorten the pre-flight list, but overall it's efficient for the complexity.

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 complexity (11 parameters, 3 required, nested objects, no output schema), the description covers all necessary aspects: purpose, usage context, behavioral details, parameter semantics, and pre-flight workflow. It is complete for an agent to select and invoke the tool 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%, but the description adds critical context beyond the schema. For example, it explains the schema parameter with an example, clarifies llm_model context lengths, warns about max_pages confirmation, and provides the pre-flight workflow that involves parameters like llm_provider and llm_api_key. This significantly aids correct parameter usage.

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 action: 'Crawl a domain and extract structured data from every page using your LLM.' It specifies the resource (domain) and the result (structured data). It distinguishes itself from sibling tools like crawl_site (no extraction) and extract_data (single page) by emphasizing multiple pages and structured fields.

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 explicitly says when to use this tool: 'when the user wants structured FIELDS from MULTIPLE pages'. It provides examples and pre-flight steps. However, it does not explicitly state when NOT to use it or directly compare with siblings, but the context is clear enough from the description and sibling list.

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