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

Annotations only declare readOnlyHint and openWorldHint, so the description must carry the rest — and it does: it names the remote artifacts fetched (/.well-known/ucp, /.well-known/acp.json, MCP server card) and states the return shape (0-100 score, readiness level, prioritized fix list). It stops short of noting fetch limits or how unreachable pages are handled, which keeps it below a 5.

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 motivating question is front-loaded, followed by a dense but scannable enumeration of checks and the return contract. It is long, but nearly every clause maps to a distinct capability, so little is 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?

With no output schema, the description compensates by spelling out the result fields (score, level, prioritized fixes) and the full audit surface. For a single-parameter, read-only audit tool, an agent has everything needed to call it and interpret the answer.

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% and the single 'url' parameter already documents both accepted forms with examples. The description reinforces that any online store or product page is in scope ('AI bot access to product pages'), adding light interpretive value but no syntax beyond the schema.

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 concrete question-and-verb framing ('Audit whether an online store is ready for AI shopping agents') and then enumerates the exact signals checked (bot access, Product structured data, policy pages, sitemap/feed, platform detection, .well-known protocol files). That specificity separates it from siblings like check_ai_crawler_access (single-signal) and ai_visibility_score (visibility, not commerce readiness), even though no sibling is named.

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?

Usage context is implied by the audit scope, but there is no explicit when-to-use/when-not guidance and no routing to alternatives such as check_ai_crawler_access, ai_visibility_score, or generate_ai_robots_txt, which overlap with parts of this check. An agent can infer the intent but must guess the boundary.

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