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

Annotations already establish the safety profile (readOnlyHint, idempotentHint, destructiveHint=false, openWorldHint=false), so the description earns credit for what it adds: the concrete shape of each returned entry and the side-signal that it also reports whether AI is configured on the server at all. That last clause matters behaviorally — a caller can learn AI is unavailable without a failed run — and is not derivable from any structured field.

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?

One sentence, front-loaded with the verb and scope, with the em-dash clause carrying only substantive content. Every clause maps to a distinct piece of returned data, so nothing is filler despite the length.

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 output schema and no parameters, the description's main obligation is to describe what comes back, and it does so field by field. Minor gap: it does not say whether the list is filtered by the caller's role (only that per-agent runnability is reported) or note any ordering/absence case such as an empty list when AI is unconfigured.

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 to disambiguate and the baseline of 4 applies. The description correctly spends no words on input semantics.

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?

States a specific verb and resource ("List the AI agents this workspace can run") and then enumerates exactly what each entry conveys: kind, projectId requirement, applyability, credit cost, and role permission. This implicitly separates it from list_agent_runs and get_agent_run, but never names those siblings, so an agent scanning a long sibling list must infer the boundary itself.

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?

No explicit when-to-use, prerequisites, or alternative is given. The natural workflow (call this before run_agent or apply_agent_run to pick an agent) is only implied by the returned fields, such as 'whether its result can be applied' and 'typical cost in credits'. Usable but left to inference.

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