lemon-squeezy-mcp

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

With no annotations provided, the description carries the full burden of behavioral disclosure. 'Issue a refund' implies a financial mutation, but it doesn't disclose critical behaviors: whether this requires specific permissions, if it's reversible, what happens to order status post-refund, or any rate limits. For a mutation tool with zero annotation coverage, this leaves significant gaps in understanding operational impact.

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, efficient sentence that gets straight to the point with zero wasted words. It's front-loaded with the core action and resource, making it easy to parse quickly. Every word earns its place 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 financial mutation tool with no annotations and no output schema, the description is inadequate. It doesn't cover behavioral traits (permissions, reversibility), output expectations (what the refund returns), or error conditions. Given the complexity and lack of structured data, more context is needed to guide safe and effective use.

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 100%, with both parameters ('orderId' and 'amount') clearly documented in the schema. The description adds no additional semantic context beyond what's in the schema (e.g., it doesn't clarify if 'amount' must be less than or equal to order total, or if 'orderId' must be valid). Baseline 3 is appropriate when the schema does the heavy lifting.

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 action ('issue a refund') and the target resource ('for an order'), making the purpose immediately understandable. It distinguishes from sibling tools like 'issue_subscription_invoice_refund' by specifying 'order' rather than 'subscription invoice'. However, it doesn't specify what type of refund (full/partial) or the scope of the operation, keeping it from a perfect score.

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 like 'issue_subscription_invoice_refund' or 'cancel_subscription'. It doesn't mention prerequisites (e.g., order must be in a refundable state) or exclusions (e.g., cannot refund already refunded orders). The agent must infer usage from the name alone.

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