ask_ezstat

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

With no annotations provided, the description carries full responsibility for behavioral disclosure. It discloses that the tool returns a grounded answer plus underlying data, which is useful. However, it doesn't mention that this is a read-only operation, any potential latency, or possible limitations of the natural-language model. The 'agent-read path' hint implies read-only but it is not explicit.

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 two sentences, front-loaded with the primary purpose, and includes a concrete example. Every sentence earns its place with no filler.

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 tool with a clear description, the definition covers the core behavior, gives examples, and states the return value. It lacks some context such as authentication requirements or error conditions, but these are not critical for an agent to select and invoke the tool correctly in most cases.

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 schema already contains a well-described query parameter with examples, and schema coverage is 100%. The description reinforces the same meaning by giving examples but does not add meaning beyond what the schema provides. The baseline of 3 is appropriate.

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 ('Ask') and resource ('the account's metrics'), and clarifies the behavior: it returns a grounded answer plus the underlying data. It distinguishes itself from siblings like read_stat and list_stats by calling itself the 'agent-read path' for natural-language questions.

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 gives clear context for when to use this tool: when the agent needs to ask a natural-language question about metrics. It provides examples of appropriate queries. However, it does not explicitly name alternative tools or state when NOT to use it (e.g., when you need a single numeric read via read_stat).

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