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

Annotations already cover the safety profile (readOnly, closed-world), so the description's value is in the semantics it adds: a fixed 14 UTC-calendar-day window, that figures are request counts rather than people or verified agents, and that labeled test traffic is excluded. These caveats materially change how an agent interprets the numbers; only the aggregation/return shape is left unstated.

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 tight sentences, zero filler, with the scope and the window front-loaded ahead of the two interpretation caveats. Every clause 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?

With no parameters and no output schema, the description carries the burden of explaining what comes back, and it names the three metric families plus the counting unit. What it omits is the response structure (field names, granularity per experiment vs total), the only remaining gap for a no-parameter reporting tool.

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?

Zero parameters, so the baseline is 4. The description correctly signals that no arguments exist by emphasizing a fixed 14-day window, which preempts an agent trying to pass a date range.

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?

Specific verb ('Read') plus a concrete resource set: aggregate traffic, MCP usage, and submission outcomes, over a defined 14-day UTC window. An agent can tell this is the results/metrics read rather than a status check, though it never explicitly contrasts itself with get_experiment_status.

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?

Usage is only implied: it is the tool you call to obtain aggregate outcomes, and the fixed 14-day window tells the agent no date filtering is available. No when-not-to-use guidance and no mention of get_experiment_status as the alternative for configuration/status questions.

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