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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint, so the safety profile is covered structurally. The description adds useful scope context ('platform-wide') and names the aggregated metrics, but says nothing about data freshness, time window defaults, or aggregation lag, which matter for a stats endpoint. An output schema exists, so the omission of return shape is acceptable.

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 sentences, zero filler. The core action and scope statement come first, and the disambiguating clause is placed exactly where it is needed.

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 parameterless aggregate-stats tool with a rich annotation set and an output schema, the description carries enough to select and call it correctly. The only modest gap is the absence of any note on aggregation window or freshness.

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?

The tool takes zero parameters, so the baseline applies and there is no parameter meaning for the description to supply. Nothing in the description misrepresents the (empty) input surface.

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 ('Get platform-wide statistics for runtime JavaScript analysis') and then enumerates the concrete metric families returned (risk distribution, eval call averages/totals, high-risk events). The closing clause 'Describes the service, not a scan' cleanly separates it from scan-scoped siblings like get_js_runtime_behaviour and get_js_runtime_coverage.

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 phrase 'Describes the service, not a scan' gives explicit scoping guidance and rules out the per-scan interpretation, which is the main ambiguity for this family of tools. It does not name a specific alternative tool to use instead for scan-level data, so it stops short of a full when/when-not/alternative treatment.

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