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upload_screenshot

Adds new screenshots for the listing: PNGs, 1366 x 768 up to 3840 x 2160, at most 50 MB each. Call it without files for a link valid for an hour, and PUT one PNG per request with the returned curl command; each upload answers with an id. In ChatGPT, which has no shell, call pick_screenshots instead, even when the person attached the PNGs to a message: its file picker passes them here as files (up to 10) and tells you the ids. Then pass the ids, in order, to set_screenshots. Uploads stay private until they are sent.

Input Schema

NameRequiredDescriptionDefault
appIdYesThe app id from list_apps.
filesNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Annotations cover the mutation/open-world profile, and the description adds substantial context beyond them: the no-files mode returns an hour-valid link, one PNG per PUT via a returned curl command, each upload answers with an id, and uploads remain private until sent. This is exactly the behavioral detail the annotations cannot 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?

Dense but front-loaded, opening with purpose before moving to modes and escalation paths. Multi-clause sentences are justified by a genuinely multi-step workflow, though it could be split more cleanly.

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?

No output schema exists, and the description fills that gap by explaining the returned id and the link behavior. Combined with the alternative-tool routing and privacy note, an agent has everything needed to invoke it correctly.

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

Parameters4/5

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

Schema coverage is 50% and the nested files fields (download_url, file_id, file_name, mime_type) are undocumented, but the description compensates with meaningful file constraints: PNG only, 1366x768 to 3840x2160, at most 50 MB each, up to 10 files. It adds real semantics for the ambiguous files parameter even if field-level meaning is not covered.

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 ('Adds new screenshots for the listing') and immediately distinguishes itself from siblings by naming pick_screenshots and set_screenshots in the workflow. An agent can tell it apart from adjacent tools without opening the schema.

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?

Explicitly routes the agent: call without files for an upload link, use pick_screenshots in ChatGPT (no shell) even when PNGs are attached, then pass ids to set_screenshots. The when-to-use and when-to-use-an-alternative conditions are both spelled out.

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

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