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Check print generation

get_studio_status
Read-onlyIdempotent

Poll a custom print generation by its print_id to check whether it is done or failed, returning the preview and shareable design URLs when complete.

Instructions

Poll a custom print started by generate_custom_print. status 'done' and 'failed' are final; anything else means still working — poll about every 30 seconds (generation takes 2–10 min) and don't start another generation meanwhile, since an account runs one at a time. When done it returns preview_url (the raw image: embed or attach it so the human sees the print) and design_url (the page to share); then offer add_custom_to_cart with the same print_id. 'failed' carries the reason, and its credits are refunded automatically. Read-only — polling costs nothing.

Input Schema

NameRequiredDescriptionDefault
print_idYesGeneration id returned by generate_custom_print; the same id goes to add_custom_to_cart.

Output Schema

NameRequiredDescriptionDefault
noteNo
errorNoGeneration failure reason (credits are refunded).
detailNo
statusNoGeneration state; 'done' and 'failed' are terminal.
print_idNo
design_urlNoShareable Studio design page (when done) — the link to SHARE with the human.
preview_urlNoRaw print image (when done) — embed/attach it so the human sees the print in chat.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.2.0
    • changedInput schema / properties / print_id / description
      Previous value: -"Generation id returned by generate_custom_print."New value: +"Generation id returned by generate_custom_print; the same id goes to add_custom_to_cart."
  2. Addedv1.1.0

TDQS

A4.6/5.0
Behavior5/5

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

Annotations cover safety (readOnly, idempotent, non-destructive), and the description adds substantial context beyond them: expected generation duration (2–10 min), the one-generation-per-account constraint, automatic credit refund on failure, and the fact that polling is free. This is exactly the kind of operational context annotations can't convey.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the core action and status semantics, and every sentence carries real value (cadence, constraint, return handling, refund behavior). It is dense and somewhat run-on — a couple of clauses could be split for scannability — so not quite a 5.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given a single required param, full annotation coverage, and an output schema, the description still goes beyond necessity by explaining preview_url vs design_url handling and the failed-state refund. Nothing an agent needs to poll correctly or act on the result is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Only one parameter, and the schema documents it at 100% coverage including that the same id goes to add_custom_to_cart. The description reinforces the print_id linkage but adds no syntax, format, or lookup semantics beyond the schema, so the baseline 3 for full coverage is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Poll a custom print started by generate_custom_print') and explicitly ties itself to the sibling that creates the resource. An agent immediately understands it is the check-status counterpart to generation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit when-to-use and next-step guidance: poll roughly every 30s, don't start another generation while one is running (account runs one at a time), and once done offer add_custom_to_cart with the same print_id. Terminal vs non-terminal statuses are enumerated, so no inference is required.

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