scrape_page

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

With no annotations provided, the description carries full burden. It discloses network interception, caching behavior, automatic session cookie management, and the absence of AI analysis. This is rich behavioral context beyond the raw schema.

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 dense paragraph, but it is front-loaded with the deprecation notice and every sentence adds meaningful detail. A bit long, but appropriate given the tool's complexity and lack of an output schema.

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 high complexity, no output schema, and no annotations, the description is remarkably complete. It covers return categories, caching, session handling, platform fingerprinting, and deprecation, leaving little ambiguity about what the tool does and its side effects.

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 baseline is 3. The description does not add parameter-level explanation, but it provides domain context about what the scraped data will contain. Since each parameter is already fully documented in the schema, 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 clearly states the tool extracts raw structured data from storefront URLs without AI analysis, enumerates the returned data categories, and explicitly marks the tool as deprecated with a direct alternative. This distinguishes it from siblings like scrape_pdp and acquire.

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 deprecation notice explicitly directs users to use 'acquire instead', providing a clear when-not-to-use instruction. It also notes that results are cached and reused by audit_storefront or ask_page, giving additional context for downstream usage.

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