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

No annotations are supplied, so the description carries the full burden; 'List' implies a safe read, and 'workspace' implies results are scoped to the current workspace configuration. It does not state whether the levels are static or workspace-customizable, nor whether any permission is required, but for a zero-parameter read this is a modest gap.

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?

A single front-loaded sentence with no wasted words. It is terse to the point of omitting routing hints, but every word 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?

With zero parameters and an output schema present, return-value explanation is unnecessary, and the description covers the core semantics. Only the relationship to update_language_formality and list_language_settings is missing.

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 sets the baseline at 4; there is no parameter meaning the description needs to compensate for. The description correctly implies no filtering input is required.

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 verb ('List') and a specific resource ('supported workspace language formality levels'), so the agent knows exactly what comes back. It does not, however, explicitly distinguish itself from nearby siblings such as list_language_settings or update_language_formality.

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?

Usage is only implied: an agent can infer this is the discovery call that precedes update_language_formality, but the description never says so or names alternatives. No when-not-to-use guidance is given, which is a clear gap for a lookup tool with many siblings.

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