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

With no annotations provided, the description carries the full burden and does useful work: it states the data is 'server-side, IP-verified', that the tool is 'Free, no auth', and describes the returned time windows and series. It does not detail response formatting or rate limits, but for a simple read endpoint this is solid disclosure.

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 compact and front-loaded: it opens with a compelling question, then explains data source, outputs, and example uses in three sentences. The only minor waste is the promotional phrase 'one of the largest networks of business pages online', but overall it earns its place.

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 one-optional-parameter, no-auth read tool with no output schema, the description is largely complete: it covers purpose, data provenance, auth requirements, time granularity, and sample queries. It does not describe the exact return schema, but that is somewhat mitigated by the clear description of what is returned.

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%, so the schema already fully documents the single optional 'days' parameter. The description adds a little context by mentioning 'daily series' and the allowed range indirectly, but it does not significantly enhance the parameter meaning 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 clearly identifies the tool's function: tracking which AI engines read business web pages, via server-side IP-verified crawler logs. It states specific output measures (per-engine reads over 10 minutes, 24 hours, all time, plus a daily series), which distinguishes it from the unrelated SEO/audit siblings.

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 provides explicit use-case examples: 'which AI crawler is most active', 'how much is Claude reading compared to GPTBot', and 'is AI crawling going up'. It does not explicitly state when not to use the tool or name alternatives, but the provided queries give clear contextual guidance.

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