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

The description frames this as a pure discovery/read ("Lists ..."), yet the annotation declares readOnlyHint=false, which suggests the tool may not be side-effect free — the two signals pull in opposite directions. Aside from that, the description adds no behavior beyond annotations: no cost, caching, or latency note for a no-parameter call, and it does not clarify the freshness of the data range it reports.

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 waste: the first states output contents, the second states the invocation rule and the sibling it depends on. The key guidance (when to call) is front-loaded enough to be read in a single pass.

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 no-parameter discovery tool with an output schema, this is essentially complete — the agent knows what it returns and when to reach for it. The remaining gap is routing among the other metric-ish siblings (data_status, derived_metrics, sessions), which the description never mentions.

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 is 4 and there is nothing the description needs to disambiguate. It does usefully note that the call returns metric names, units, and data history depth, which is more than the empty schema conveys.

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?

"Lists the available health metrics, the unit of each one, and how far back the data goes" names a specific verb (lists) and resource (health metrics) and even previews the three fields returned, so an agent knows exactly what it gets. It does not distinguish itself from near-neighbours such as data_status or derived_metrics, which also sound like metric-discovery tools, so it stops short of full sibling differentiation.

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 gives an explicit trigger and a named alternative: "Call this before query_daily if you do not know the exact metric names." That is a clear use condition tied to a concrete sibling. It lacks a when-not clause (e.g., skip it if names are already known, or use data_status for coverage/freshness questions), so it is short of a 5.

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