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

Annotations already declare readOnlyHint, idempotentHint and destructiveHint=false, so safety is covered structurally. The description still earns credit by disclosing the non-obvious behavior that it 'opens nothing by itself' and only returns procedural guidance, which is exactly the fact an agent would otherwise get wrong given the 'list' name. It does not describe the shape or size of the returned instructions.

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?

The core is two compact clauses, but the opening 'from ChatGPT, Claude or any AI agent' is filler and the trailing 'Kahunas's official API: Kahunas publishes no API docs' is garbled and redundant. The semicolon-joined middle sentence packs the workflow and the no-side-effect warning together in a way that reads awkwardly.

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 carries the burden of explaining what comes back, and it does: step-by-step screens, buttons and fields, plus the instruction to then execute with cotlet_browser_*. What is missing is any sense of the return size or how to handle a failed navigation when the follow-up browser steps are performed.

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 there is nothing for the description to disambiguate and the baseline of 4 applies. No misleading parameter claims are made.

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 a concrete verb and resource (list clients in the user's Kahunas account) and then immediately corrects the likely misreading of the name by stating it returns step-by-step instructions rather than client data. That distinction is the most useful thing an agent can know here. It stops short of naming which sibling to prefer, so it is clear but not sibling-differentiated.

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 implies a two-step workflow: call this to learn the screens/buttons/fields, then act via cotlet_browser_* tools in the Kahunas Cloud Browser. That is real usage context, but there are no explicit when-to-use vs when-not conditions and no routing to alternatives such as cotlet_app_guide for a general app overview. The 'from ChatGPT, Claude or any AI agent' clause adds no selection guidance.

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