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

Annotations already cover the read-only, closed-world profile, so the bar is low. The description still adds real context by stating it 'Reads no catalog,' signalling deterministic, side-effect-free output that does not touch live data. It does not describe the response shape, keeping it just short of 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?

Five short sentences, front-loaded with the identity mapping and the usage rule, with no padding. The telegraphic fragments ('No parameters. Reads no catalog.') read abruptly, and the parameter note restates the schema, so it is efficient rather than exemplary.

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 static, zero-parameter comparison tool with no output schema, the description tells the agent what it will learn and when to reach for it. The only minor gap is that it does not hint at the return format of the comparison.

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, which is the baseline-4 case. The explicit 'No parameters' statement is redundant with an empty schema object but consistent and harmless.

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 names the specific subject (the distinction between Crovia and Causari) and defines each product's role — Crovia for training-data disclosure, Causari for code provenance — so an agent knows exactly what question this answers. It falls short of 5 because the opening fragment 'Which product is which' is terse and the true purpose only emerges in the following two sentences.

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 routing rule: 'Use this, not explain and not crovia_status, when the question is the difference between the two.' Both the alternative tools and the selecting condition are named, leaving nothing to inference.

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