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

Annotations already declare the safe read-only, idempotent, non-destructive profile, so the bar is lower. The description still adds genuinely useful behavioral context — that the output is a monthly time series of two specific margin measures rather than a single value — which is not derivable from the annotations or the empty schema. It does not mention the time window covered or any row limits, so it falls short of a 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?

Three sentences, front-loaded with what the tool returns before routing guidance, with no filler. Every sentence earns its place: content, when-to-use, and alternatives.

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 must convey what comes back, and it does (monthly gross margin and margin-after-spend). It omits the time span or history depth the series covers, which an agent would want to know before promising 'history' to a user.

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 schema baseline is 4 and there is nothing for the description to clarify. No parameter syntax or defaults are misrepresented.

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 resource (gross margin and margin-after-spend) and its granularity (month by month), and explicitly names the two siblings it is not — get_contribution_breakdown and get_vertical_benchmarks. An agent can distinguish it from all 23 siblings 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?

It gives explicit trigger conditions ('whether a margin is normal, when it changed, or how it compares with earlier periods') and names the two alternative tools with the conditions that select them (single-period structure, industry range). Nothing is left to inference.

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