compare_storefronts

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It explicitly states that the tool scrapes URLs, discloses caching behavior ('reuses cached page data if either URL was scraped in the last 10 minutes'), and lists the exact outputs. This goes well beyond what a minimal description would provide and gives the agent a strong basis for predicting side effects and performance.

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 three sentences, front-loaded with the primary action, and uses compact list-style phrasing for the diff components. Every sentence earns its place, and the caching note is efficiently integrated into the final sentence. There is no fluff or redundancy.

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?

Despite the absence of an output schema, the description enumerates all major return components, covering product count, facets, trust signals, sort options, B2B mode, and performance. It also mentions caching behavior and the default product count context. This is sufficient for an agent to understand what the tool produces and how it behaves, even without an output schema.

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 description coverage is 100%, with clear descriptions for url_a, url_b, and max_products. The tool description adds overall context about the diff output but does not add meaningful parameter-level semantics beyond what the schema already provides. A baseline of 3 is appropriate because the schema handles parameter explanation fully.

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 opens with a specific verb ('Scrape') and a clear resource ('two storefront URLs'), then enumerates the exact comparison dimensions returned (product count delta, facet gaps, trust signal coverage, sort option gaps, B2B mode, performance delta). This clearly distinguishes it from sibling tools like scrape_pdp or scrape_page, which focus on individual pages rather than side-by-side storefront comparisons.

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 makes the use case explicit: comparing two storefront URLs and receiving a structured diff. It does not explicitly state when not to use it or name alternatives, but the detailed output summary and the caching note imply a comparison workflow that is distinct from the sibling scraping tools. It provides clear context without exclusions, which fits a 4.

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