subscriptions__mrr_summary

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

No annotations are provided, so the description carries the full burden. It discloses that the tool returns aggregate data and does not expose identifiers, which is useful. However, it omits details about response structure, error conditions, or whether it is a safe read operation, which is important since no behavioral annotations exist.

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 with a concise prefix label. Every word contributes meaning: it specifies the domain, what is returned, and what is not included. No waste.

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 no parameters and no output schema, the description covers the key aspects: aggregate metrics and exclusion of identifiers. It could be enhanced by noting whether authentication is required or if the data is scoped to a specific workspace, but it is largely sufficient for a summary endpoint.

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 input schema has zero parameters, and schema coverage is 100% trivially. The description adds context that the tool aggregates active live-mode subscriptions, which clarifies what data is being summarized. Since there are no parameters to describe, a baseline of 4 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 clearly states the tool returns aggregate active live-mode subscription count, MRR minor units, and plan mix. It specifies the scope (B2B monthly seats, entitlement quota, overage) and explicitly mentions what is NOT exposed (no account or Stripe identifiers). This distinguishes it from other subscription tools.

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 mentions it returns aggregate data and excludes identifiers, implying it is for high-level summaries rather than detailed per-subscription queries. However, it does not explicitly state when to use this tool versus alternatives like subscriptions__subscription_status or subscriptions__usage_summary, leaving some ambiguity.

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