check_ai_visibility

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

With no annotations, the description carries the full burden and does well: it declares 'Read-only: nothing is created, purchased or uploaded,' explains that raw HTML rather than rendered DOM is fetched (because AI crawlers do not run JavaScript), and distinguishes crawler classes. It omits runtime, rate-limit and cost expectations for a multi-page crawl.

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?

Purpose is front-loaded and the numbered checks are easy to scan, but the crawler lists and parenthetical rationales make the single paragraph dense and longer than strictly needed. Every sentence does carry information, so nothing is pure padding.

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?

For a 3-param, annotation-free tool with no output schema, the description covers scope, method and safety profile well. The main gap is return-shape detail (what findings or scores come back), which nothing else supplies since there is no 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 coverage is 100%, so baseline is 3, but the description adds real meaning beyond the schema — why the product-page URL check targets raw HTML and why sampling N pages matters for distinguishing a systemic problem from a one-off. It still adds no syntax or format detail beyond the schema examples.

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?

Opens with a specific verb plus resource and scope: 'Check whether AI assistants can find, read and transact with an ecommerce store.' The three enumerated checks make the deliverable unambiguous, and the read-only sentence distinguishes it from any mutating sibling.

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 gives clear context for when the tool applies — auditing AI/agent discoverability of a store — and enumerates the three surfaces checked. It does not explicitly name when to prefer it over the lone sibling build_recommendation_test, so it stops short of full routing guidance.

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