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

Annotations already declare readOnly/idempotent/non-destructive, but the description adds genuinely non-obvious behavior: the call returns procedural guidance rather than data and performs no action, so the agent must chain into cotlet_browser_* to accomplish anything. It also preempts a dead end by noting the official REST API and reporting MCP server do not cover day-to-day admin work. Missing: whether a browser session or linked account must already exist before this is useful.

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-loads the key behavior correction, which is good, but pads with 'from ChatGPT, Claude or any AI agent' and a dated competitive-API justification ('checked 20 Oct 2026') that reads as marketing rather than operational guidance. The useful content could be delivered in about half the words without losing meaning.

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 well: it tells the agent what comes back (step-by-step screens, buttons, fields), what does not happen (nothing is opened), and what to do next. The only meaningful gap is preconditions for the follow-up browser session.

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 no parameter meaning to convey and the baseline of 4 applies. The description correctly implies the scope is fixed to the user's own account, which is the only 'parameter-like' constraint an agent needs to understand.

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?

Names a specific verb+resource (list users in LearnUpon) and then immediately corrects the expectation set by the name: it returns step-by-step instructions (screens, buttons, fields) rather than user data, and opens nothing itself. That clarification is the decisive detail an agent needs. It does not differentiate itself from the sibling LearnUpon guides (e.g. learnupon_list_enrollments), so it stops short of a 5.

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 a usable workflow: read this guide first, then perform the action with cotlet_browser_* tools in the user's LearnUpon Cloud Browser. It never states when NOT to use it, nor how it differs from the other learnupon_* guide tools that presumably behave the same way, so an agent facing multiple LearnUpon tools still has to guess which guide applies.

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