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

Annotations mark it read-only and open-world, and the description goes well beyond them: ~3 minute runtime, progress reported as answers stream in, free-tier rate limits (two new websites per hour per network address, shared by hosted clients, plus a daily cap), and the caching nuance that a city or category makes an already-scanned website a new scan. These are exactly the operational facts an agent needs before committing to a three-minute call.

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?

Front-loaded with the core verb and scope in the first clause, then layered with output, duration, and limits in a logical order. It is a single dense run-on paragraph, though, so the rate-limit and re-scan details take a careful read to parse.

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 five params, no output schema, and open-world behavior, the description covers everything material: what gets returned (naming frequency, score out of 100, competitors, blockers), how long it takes, how progress surfaces, and the quota constraints. Nothing an agent needs before invoking is missing.

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 the baseline is 3, but the description adds real meaning: it explains that website is the object being read and that city/category act as scan-identity keys ('a city or category makes it a new scan, even of a website scanned before'). Only language goes unaddressed in prose.

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?

States a specific action and scope: runs a free AI visibility scan of one business, detailing exactly what the scan does (reads site, writes buyer questions, queries ChatGPT/Claude/Gemini/Grok, reports naming frequency, a score out of 100, competitors and blockers). This is far more specific than 'check visibility' and lets an agent distinguish a full multi-model scan from the lighter siblings ai_index_lookup and get_score.

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 clear this is the full free scan (implying the siblings are for narrower lookups) and notes that adding a city or category forces a new scan, which is a useful selection cue. However, it never explicitly names when to use this versus get_score or ai_index_lookup, so routing is left to inference.

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