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

With no annotations provided, the description carries the full burden of disclosing behavior. It correctly implies this is a read-only operation (a getter), which is safe. However, it does not explain what happens when the optional organization_id is omitted (whether it defaults to the authenticated org, errors, or returns aggregate data). It also does not mention any authentication requirements or rate limiting. The lack of detail on the optional parameter's behavior is a notable gap.

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 a single sentence, which is concise and front-loads the primary purpose (consumption vs plan limits). However, the long list of usage categories runs together without bullets or separators, making it slightly harder to parse quickly. It is efficient but could benefit from light structuring, such as commas or a colon, to improve scannability.

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 no output schema, the description covers the return content well by enumerating the metrics. However, it is incomplete regarding the optional parameter: an agent cannot infer whether organization_id is required in practice, what a null value means, or if the response is aggregated or per-org. There is also no mention of the response format (e.g., JSON structure) or any pagination, though that may be acceptable given the absence of an output schema. Overall, it is sufficient for a basic understanding but leaves a key gap around the parameter.

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%, so the description must compensate for the parameter's meaning. The description does not mention organization_id at all. The schema only lists the parameter as an integer with no description, and it is optional. The tool's core purpose (usage vs limits) suggests the organization_id likely scopes the query, but the description offers no explanation, leaving an agent to guess at the parameter's role and possible values.

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 returns monthly usage vs plan limits, enumerating the specific categories (keyword searches, audit credits, AI Presence credits, backlinks, competitor analysis, keyword monitoring, MCP action cap). It uses a specific resource ('usage') and context ('vs plan limits'), which distinguishes it from other get_* tools that focus on data outputs rather than consumption quotas. However, it does not explicitly name an alternative or contrast itself with siblings, so it stops short of a 5.

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 implies when to use this tool (to check quota consumption against limits), but it provides no explicit when-to-use, when-not-to-use, or alternative routing. There is no mention of scenarios where a different tool might be more appropriate, nor prerequisites like needing an organization context. The guidance is left to inference from the name and description.

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