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

Annotations only declare readOnlyHint=true, so the description carries most of the burden and does add real context: it explains the conditional `channels` field for 1P accounts and decodes each `basis` value (sell-out/sell-in/purchase-orders/stock). It does not cover output shape beyond field names or note any size/rate limits, keeping it below 5.

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 core purpose and the 'call this first' directive, then structured into a clearly scoped elaboration. The Vendor Central paragraph is dense and long relative to the tool's simplicity, but every clause conveys semantic meaning 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?

There is no output schema, so the description must explain what comes back — and it does, enumerating the four core fields plus the conditional `channels` and `basis` semantics. Nothing an agent needs to interpret the result and pick a metric key 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 a single parameter and schema description coverage is 100% — the `reason` field is fully documented in the schema, including the English-only and recording rationale. The description adds nothing about it, so the baseline 3 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 ('List the metrics Nova can report') and immediately enumerates the returned fields (key, label, unit type, higher-is-better), which distinguishes it from siblings like query_metrics and describe_metric. An agent knows exactly what this returns without opening any schema.

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 an explicit sequencing directive: 'Call this first to discover valid metric keys for the other tools.' That is a clear usage context. It stops short of naming alternatives (e.g., describe_metric for per-metric detail) or stating when-not to use it, so it falls 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.