Shopify MCP Server

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. It states the tool 'shows spend per event for a date range,' which implies a read-only operation, but doesn't clarify permissions, rate limits, data freshness, or what happens with invalid dates. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior and constraints.

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 extremely concise and front-loaded: two sentences that directly state the tool's function and scope without any fluff. Every word earns its place, making it easy for an agent to quickly grasp the core purpose.

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 moderate complexity (2 parameters, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose and scope but lacks details on behavioral traits, output format, or error handling. Without annotations or output schema, the agent must infer these aspects, leaving room for uncertainty in 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 schema description coverage is 100%, with both parameters (since, until) well-documented in the schema regarding format and defaults. The description adds minimal value beyond the schema by mentioning 'date range' but doesn't provide additional context like timezone handling or event filtering. Baseline 3 is appropriate since 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 tool's purpose: 'Get ad spend from Shopify marketing events' with specific resources (Shop campaigns) and scope (per event for a date range). It distinguishes itself from siblings like shopify_sales_by_channel or shopify_shop_campaign_insights by focusing specifically on ad spend metrics rather than sales or broader insights. However, it doesn't explicitly contrast with all siblings, so it's not a perfect 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 provides no guidance on when to use this tool versus alternatives. It doesn't mention when to choose this over siblings like shopify_shop_campaign_insights or shopify_sales_by_channel, nor does it specify prerequisites or exclusions. The context is implied (date-range analysis of ad spend) but lacks explicit usage instructions.

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