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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds the scoping fact that results are limited to the base's own workspace, which is genuine context, but it says nothing about return ordering, size, pagination, or what happens when the workspace has no AI services enabled.

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 tight sentence with no filler, and the high-value consumption hint (options.ai.service) is placed inline. The phrasing is somewhat elliptical — a sentence fragment without an explicit verb — but nothing is wasted.

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?

For a simple one-parameter read tool with no output schema and no nested objects, this is close to sufficient: the agent knows what the call returns in kind and where to use the results. It still leaves the parameter unnamed and gives no sense of the returned fields (id, name), which matters for a tool whose whole purpose is feeding IDs into other calls.

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?

Schema description coverage is 0% and the sole required parameter, baseId, is never mentioned by name in the description. The phrase 'of the base's workspace' only obliquely implies that the base scopes the result set; an agent gets no confirmation that baseId is the selector or what the accepted identifier format is.

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 the resource precisely — model services of the base's workspace — and adds where those values are consumed (options.ai.service and AI automation steps), which makes the payload's purpose unmistakable. It lacks an explicit 'List' verb in prose, but the resource plus the name make the operation clear and distinct from siblings like list_automations or describe_base.

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 implied rather than stated: the mention of 'options.ai.service' and 'AI automation steps' suggests calling it to discover valid service identifiers before configuring an AI field or automation, but there is no explicit when-to-use, no prerequisites, and no named alternative among the 25 siblings.

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