list_environments

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It describes the response format, which adds some value, but fails to cover critical aspects like whether this is a read-only operation, potential rate limits, authentication requirements, or error handling. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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?

The description is front-loaded with the main purpose in the first sentence, followed by a clear breakdown of the response format. Every sentence adds value without redundancy, making it efficient and easy to parse. The structure is logical and concise, with no wasted words.

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?

Given that the tool has 0 parameters, 100% schema coverage, and an output schema exists (implied by the response description), the description is moderately complete. It explains the return values, which compensates for the lack of output schema details. However, without annotations and with no usage guidelines, it falls short of being fully comprehensive for effective tool invocation.

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 has 0 parameters, and the schema description coverage is 100%, so there is no need for parameter explanation in the description. The baseline score for such cases is 4, as the description appropriately avoids redundant information and focuses on other aspects like the response structure.

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 clearly states the tool's purpose: 'Return configured Prometheus environments and their base URLs.' It specifies the verb ('Return') and resource ('configured Prometheus environments and their base URLs'), making the function evident. However, it does not explicitly differentiate from sibling tools like 'list_loki_environments', which might cause confusion in usage context.

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 description provides no guidance on when to use this tool versus alternatives. It lacks context such as prerequisites, when it should be used over similar tools like 'list_loki_environments' or 'list_servers', and any exclusions or specific scenarios for its application. This absence of usage instructions could lead to incorrect tool selection by an AI agent.

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