Get the print-validation report for an uploaded PDF before paying: page count, trim size, hard errors (blocking) and soft warnings (non-blocking). Every error includes a resolution explaining how to fix it. Free to call; use it to check printability before create_order.
| Name | Required | Description | Default |
|---|---|---|---|
| upload_id | Yes | The upload_id returned by create_upload. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully discloses key behavioral traits: it is a read-only report, free, and distinguishes blocking errors (hard) from non-blocking (soft). Also reveals that errors include a resolution field, which is not obvious.
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 sentences, front-loaded with purpose, and every clause adds value (contents, blocking nature, cost, usage timing). No redundancy or fluff.
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 single-parameter tool with no output schema, the description is complete: it states what the report contains, the meaning of errors, and when to call it. No critical gaps remain.
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% for the single parameter upload_id, already describing it as returned by create_upload. The description adds no parameter-specific semantics beyond mentioning 'uploaded PDF', so baseline 3 is appropriate.
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?
States a specific verb ('Get') and resource ('print-validation report for an uploaded PDF'), and enumerates report contents (page count, trim size, hard errors, soft warnings). Clearly distinct from siblings like create_order or get_order by positioning it as a pre-payment check.
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?
Explicitly says to use it 'before paying' and 'to check printability before create_order', giving clear temporal and contextual guidance. Also notes it is 'Free to call', informing cost/usage decisions.
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.
Each tool has a clearly distinct purpose: upload, validate, create order, get order, cancel order, list catalog, and enterprise application. There is no overlap between any two tools, making misselection highly unlikely.
All tool names follow a consistent verb_noun pattern in snake_case (e.g., create_upload, cancel_order, get_catalog). The verbs are descriptive and the resources are clear, creating a predictable and uniform naming convention.
With 7 tools, the server is well-scoped for its purpose. It covers the complete print-order workflow without redundancy or excessive granularity, making the tool set easy to navigate.
The tool set covers the entire lifecycle from catalog browsing and upload validation through order creation, status tracking, and cancellation, plus enterprise account provisioning. There are no obvious missing operations that would hinder an agent in completing standard tasks.