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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is covered. The description adds substantial behavioral context beyond annotations: the cost is free on both meters, matches_available is the meter that stops metered calls, rate_limit_units_used is a separate request count not a credit figure, and unmetered accounts have null matches_available. This explains edge-case behavior (null vs zero) that an agent needs to interpret the response correctly.

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 well-structured and front-loaded: the first sentence states the core purpose, the second gives cost and usage guidance, and the following sentences explain the two meters and the unmetered edge case. Every sentence earns its place, and the structure moves from high-level purpose to specific behavioral details without redundancy.

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 zero-parameter, read-only tool with no output schema, the description is complete. It explains what the tool returns, how to interpret the two key fields, the cost implications, and the edge case for unmetered accounts. An agent has everything it needs to call the tool and interpret the result correctly. The absence of an output schema is compensated by the description's explanation of the return fields.

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 zero parameters, so the schema provides no parameter semantics to clarify. The description compensates by explaining the meaning of the two key output fields (matches_available and rate_limit_units_used), which is the closest analog to parameter semantics for a no-input tool. Baseline 4 is appropriate for zero-parameter tools, and the description adds value by defining the output 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?

The description clearly states the tool's purpose: reporting how many match credits the configured key has left and how much of the request allowance it has used. It names the specific resources (matches_available and rate_limit_units_used) and distinguishes itself from sibling tools by explaining it is a read-only meter tool, unlike resolve/reverse tools that spend credits.

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 explicitly says when to use this tool: 'Call it before a reverse lookup, which can spend up to 100 credits in one go.' It also explains when the tool remains useful (when a key is drained, this tool and coverage tool keep answering), providing clear context for choosing it over alternatives. It doesn't name a specific sibling alternative, but the usage context is explicit and actionable.

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