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

With no annotations, the description carries the full burden, and it does disclose what is inspected (multiple outbound checks against robots.txt, sitemap, llms.txt, feed, MCP endpoint). It says nothing about whether network requests are made, authentication/rate-limit constraints, or how long a full crawl of these artifacts takes, which matters for a tool that evidently reaches out to a live domain.

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?

Two sentences, zero filler. The checks are front-loaded in the first sentence and the usage trigger follows immediately. Every clause carries information an agent can act on.

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 low-complexity, single-parameter tool the description covers purpose and trigger well. But there is no output schema and no mention of the result shape, so an agent cannot anticipate whether it receives a per-crawler pass/fail breakdown or a single verdict — a meaningful gap for a multi-check diagnostic.

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?

Only one parameter (url) and schema description coverage is 100%, so the schema already documents its meaning and format example. The description adds nothing beyond that, so the baseline of 3 applies — no penalty, but no extra value either.

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 names a specific diagnostic verb and resource (discover/parse a store for AI agents) and enumerates the concrete checks performed: robots.txt per named AI crawler, sitemap, llms.txt, product feed, MCP endpoint, and catalogue machine-readability. This clearly differentiates it from siblings like audit_product_feed or check_structured_data, which cover only one facet each.

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?

It gives a clear triggering context: 'Use this when asked why a store never appears in AI assistants or agent shopping results.' That is a strong, recognizable situation. However, it names no alternatives or exclusions, even though audit_product_feed and check_structured_data overlap on sub-checks, leaving the agent to infer when the narrower sibling is preferable.

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