Shopify MCP Server

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool 'Get[s] sales breakdown' and shows discount-driven revenue, implying a read-only operation, but doesn't clarify if it requires authentication, has rate limits, returns paginated results, or what the output format looks like (e.g., list, aggregated data). For a tool with no annotations, this leaves significant gaps in understanding its behavior.

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 appropriately sized and front-loaded: two concise sentences that directly state the tool's purpose and value ('Shows which discounts are driving the most revenue'). There is no wasted text, repetition, or unnecessary elaboration, making it efficient for an agent to parse.

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 the tool's complexity (3 parameters, no output schema, no annotations), the description is incomplete. It lacks details on output format, behavioral traits like authentication or rate limits, and usage guidelines compared to siblings. While it states the purpose clearly, it doesn't compensate for the missing structured data, leaving the agent with insufficient context for effective tool selection and invocation.

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 description adds no parameter-specific information beyond what the input schema provides. With 100% schema description coverage, the schema already documents 'since', 'until', and 'limit' parameters clearly. The description doesn't explain how these parameters affect the sales breakdown (e.g., date filtering logic) or provide additional context, so it meets the baseline of 3 for high schema coverage without adding value.

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: 'Get sales breakdown by discount code' specifies the action (get) and resource (sales breakdown by discount code). It distinguishes from siblings like 'shopify_sales_by_product' or 'shopify_sales_by_channel' by focusing on discount codes. However, it doesn't explicitly contrast with 'shopify_sales_summary' or 'shopify_custom_query', which might offer overlapping functionality, preventing 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 explicit guidance on when to use this tool versus alternatives. It mentions 'Shows which discounts are driving the most revenue,' which implies a use case but doesn't specify prerequisites, exclusions, or compare it to siblings like 'shopify_sales_summary' for high-level metrics or 'shopify_custom_query' for custom analyses. Without such context, the agent must infer usage based on tool names alone.

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