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

Annotations already cover the safety profile (readOnlyHint=true, destructiveHint=false, openWorldHint=true), and the description adds meaningful behavioral context beyond them: the scan list is read at query time, and it disambiguates three response states — missing activation, measurement failure, and real data — stressing that a failure is neither 'not activated' nor an all-clear. No contradiction with the annotations.

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?

It opens with the user-facing question it answers and front-loads the core behavior before the sibling routing and edge cases. It is dense and slightly heavy on emphasis ('ZULETZT TATSÄCHLICH GELAUFENEN', 'GENAU DAS'), but each sentence carries a distinct behavioral nuance rather than 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?

With no output schema, the description carries the burden of explaining what comes back (individual findings, recommendations, overall scan value) and does so, plus it covers the ambiguous outcome states an agent must interpret. Nothing needed to call and interpret the tool 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?

There is only one parameter (domain) and schema description coverage is 100%, so the schema already carries the semantics. The description adds no domain format or syntax detail beyond the schema's own example 'example.com', making this the baseline case where structured data does the work.

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 states a specific verb+resource: the individual findings of the last actually-run turbometrics scan, with per-item recommendations (images, JS load, caching, server response time) plus that scan's overall score. It is unmistakably distinct from get_performance_score (cached nightly value) and get_performance_alerts (open monitoring warnings).

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 explicitly names the alternatives and the condition for each: a run triggered via start_performance_scan shows up here first, the cached nightly value lives in get_performance_score, and open warnings belong to get_performance_alerts. It even explains why the two numbers can diverge, leaving nothing to inference.

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