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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered. The description adds real value with the platform constraint and the note that training is local-only, which explains why the listing is local. It does not say what happens on unsupported platforms or whether the list can be empty.

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?

Two short sentences, platform constraint front-loaded, zero filler. The second sentence is terse to the point of ambiguity, which is the only deduction.

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?

An output schema exists, so return values need not be described. Still, for a zero-param tool the description is the only place to explain what a 'Teach base' is and what the agent should do with the list, and it does not.

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; baseline 4 applies. Schema coverage is 100% regardless.

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?

It gives a specific verb ('List') and a resource ('local Teach bases') plus a platform qualifier, so the shape is right. But 'Teach bases' is undefined jargon and no sibling tool is named for contrast, leaving the agent to infer what a Teach base actually is.

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?

The parenthetical '(Apple silicon, macOS 14+)' implies a prerequisite but never says when to call this versus alternatives like get_teach_template. The second sentence hints at a local-only scope but frames it obliquely ('Hosted tools do not train') rather than as a when-to-use rule.

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