Preview Shopify Admin GraphQL mutation

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 key non-execution behavior and lists the output (variables, scopes, IDs, change summary, confirmation token). This goes beyond a simple 'validates' by explaining what the user can expect, though it omits details like error handling or rate limits.

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, tightly worded sentence. It front-loads the most critical information (validates, does not execute) and lists the key return values efficiently. There is no wasted verbiage.

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 and absence of output schema or annotations, the description covers the essential aspects: what it does, what it returns, and the confirmation token. It does not explain how the token should be used for a subsequent execution, but that is outside the immediate scope of a preview tool. Overall, it provides enough context for an agent to invoke the tool correctly.

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 has zero description coverage for its three parameters. The description does not explain the query, variables, or operationName parameters beyond the tool's overall purpose. It does not add syntax, format, or usage details for these inputs, leaving the agent to infer from the parameter names alone.

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 validates but does not execute a Shopify mutation, using a specific verb ('validates') and resource ('Shopify mutation'). It also differentiates from the sibling execute_mutation by explicitly noting it does not execute, making the purpose unambiguous.

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: when you need to validate or preview a mutation without executing it. The contrast with execute_mutation is implicit rather than explicit, but the context is clear enough that an agent would know to use this for dry-run validation.

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