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

With no annotations, the description carries the load and does well: it discloses the async model ("Queue", results via get_findings), the rendering mechanism, and the connector-independence. It doesn't mention runtime/duration, rate limits, or whether repeated scans are idempotent, but the essential behavioral profile for a scan is present.

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 action and purpose, then the detection list, then the result path. The long enumeration of checks is dense but each item conveys real capability; slightly verbose but nothing is redundant filler.

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?

No output schema exists, and the description compensates by pointing to get_findings for results, plus explaining the async queue model and the no-connector case. An agent has enough to call it and retrieve results; only timing/expectations around the async queue are left implicit.

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?

There is a single parameter with 100% schema coverage, and the schema already explains it ("Site id from list_sites"). The description adds no additional meaning about site_id, so the baseline 3 for high-coverage schemas applies.

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 verb and resource ("Queue an OUTSIDE-IN front-end scan") and immediately differentiates it from server-side probes by explaining it renders in a real headless browser with JS executed. The enumerated detection categories make the tool's scope unmistakable against siblings like scan_site or probe.

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?

Gives clear context for use: "catching what server-side probes miss" tells the agent this is the complement to server-side scanning, and "Works even without the connector" removes a common prerequisite doubt. It stops short of explicitly naming scan_site/probe as the alternatives to pick instead, so the routing is inferred rather than stated.

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