printify_list_ordersList orders in a shop (paginated), optionally filtered by status or SKU. Printify REST: GET /v1/shops/{shop_id}/orders.json.
| Name | Required | Description | Default |
|---|---|---|---|
| sku | No | Filter to orders containing this SKU. | |
| page | No | 1-based page number. | |
| limit | No | Items per page (default 10, max 10). | |
| status | No | Filter by fulfillment status, e.g. 'fulfilled'. | |
| shop_id | Yes | Shop id — required. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations include readOnlyHint: true, which covers safety. The description adds that results are paginated and filterable, which is useful behavioral context. However, it does not disclose returned data structure, rate limits, or any unusual behaviors. Given the readOnlyHint, a score of 3 is appropriate.
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?
Two concise sentences, front-loaded with the core action and followed by the REST endpoint. No wasted words or redundancy with the schema. Excellent brevity.
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?
The tool is a relatively straightforward paginated list, and the description covers the core behavior. However, without an output schema, it does not explain what the response contains (e.g., order array, pagination metadata). Given the simplicity, this is a minor gap but not severe.
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 coverage is 100%, so parameters are already well-described. The description adds a high-level summary of filtering by status or SKU, but no new syntactic details beyond the schema. This aligns with the baseline of 3 when 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 lists orders in a shop, with pagination and optional filters by status or SKU. The verb 'list' and resource 'orders' are specific, and the REST endpoint adds precision. This distinguishes it from siblings like get_order (single order) and list_products (different resource).
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 usage for fetching multiple orders with optional filters, but it does not explicitly contrast with alternatives like get_order for a single order. No when-not-to-use guidance is provided, but the pagination/filter hints give reasonable context for when this tool is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Every tool targets a unique resource and action, with clear distinctions between 'get' and 'list' operations for related entities (blueprints, products, orders) and separate tools for shipping quotes, publishing, and webhooks. Descriptions further clarify any potential overlap, such as 'get_print_providers' versus 'list_print_providers'.
All tool names follow a consistent 'printify_<verb>_<noun>' pattern, using singular nouns for single-resource operations and plural for listing operations. This predictable structure makes it easy to guess tool names and understand their purpose.
With 14 tools, the set is well-scoped for the Printify domain, covering catalog data (blueprints, providers, variants), shop resources (products, orders, uploads, webhooks), and key actions (shipping quotes, publishing). The count is within the ideal range and each tool serves a distinct function.
The server provides comprehensive read operations for all major resources and includes publishing, but it lacks create/update/delete tools for products, orders, uploads, and webhooks. This limits the agent to monitoring and publishing workflows rather than full lifecycle management, leaving notable gaps for a complete Printify integration.