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

The annotations already declare readOnly, idempotent, non-destructive, and non-open-world, and the description's "opens nothing by itself" is consistent with that, so no contradiction. It adds genuinely behavioral information beyond annotations: that the return value is a step-by-step guide with screens, buttons, and fields, which tells the agent not to expect the operation to have happened. It says nothing about auth state, rate limits, or what happens if the Cloud Browser session is not available.

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 compact sentences, front-loaded with the purpose and the "opens nothing by itself" caveat before the workflow pointer. The closing sentence about the official API is slightly defensive and the parenthetical "(checked 20 Oct 2026)" is noise, but the bulk earns its place.

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?

The annotations are rich and there is no output schema to account for, and the description covers what is returned and what to do next. The significant gap is that with zero parameters the definition never states how the users to unenroll are conveyed, nor what the step-by-step output actually looks like. Adequate to call correctly, not complete.

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?

With zero parameters there is nothing for the schema to describe, so the baseline of 4 would normally apply. However, the description never explains how the target users are identified given the tool takes no arguments — presumably from conversation context — which is the one parameter-adjacent fact an agent needs. That omission pulls it below the no-param baseline.

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?

"Unenroll users in the user's own LearnUpon account" gives a specific verb and resource, and the follow-up sentence crucially clarifies that the tool returns step-by-step instructions rather than performing the action, correcting the impression created by the name. It stops short of naming which sibling to prefer for related flows (e.g. enroll_users_on_course, set_enrollment_complete), so differentiation is only partial.

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 explicitly routes the agent to a next step ("then do it with the cotlet_browser_* tools in the user's LearnUpon Cloud Browser") and rules out two obvious alternatives by noting that LearnUpon's REST API and reporting MCP server do not cover day-to-day admin work. What is missing is a positive condition such as "use when the user asks to remove a learner's enrollment" and any exclusion versus the sibling LearnUpon tools.

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