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UiChemy AI Website Creator

uichemy_upload_ticket

A way to upload pictures you have ON DISK without retyping them as base64. uichemy_upload_image is the right tool for a picture you generated as bytes, but its payload travels through the model a token at a time, so a folder of photos costs minutes and arrives shrunken. This hands back a short-lived ticket and a curl line: the bytes go straight from the file to our storage, at full size, and never enter the conversation. Same pipeline as the image panel (WebP, content-hashed, R2), so the result is indistinguishable downstream. The ticket lasts 10 minutes, is fixed to THIS project, and is write-only — it reads nothing. Each upload answers with the stored url; pass those to uichemy_set_images.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNoHow many files you are about to upload. Default 40, which is also the cap.
prefixNoWhere the files are filed. Default uploads; use logos for a brand mark.
projectIdYesThe project the pictures belong to.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Annotations only cover the safety trinity (readOnlyHint=false, destructiveHint=false, openWorldHint=false). The description adds materially: ticket is 10-minute TTL, pinned to THIS project, write-only, bytes bypass the conversation at full size, and the storage pipeline (WebP, content-hashed, R2) matches the image panel. Consistent with, not contradicting, annotations.

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 purpose and the sibling contrast, then rationale and constraints. Information-dense but slightly long; every sentence carries distinct value (why, mechanism, scope, TTL, return).

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, so the description carries the return contract and does so ('each upload answers with the stored url; pass those to uichemy_set_images'), plus the async/ticket workflow and its expiry. Nothing needed to invoke it correctly 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?

Schema description coverage is 100%, so count/prefix/projectId are already documented in the schema. The description reinforces projectId scoping ('fixed to THIS project') but adds no syntax or format detail beyond that, so the baseline of 3 applies.

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?

Specific verb+resource: it hands back a short-lived upload ticket so files on disk can be pushed straight to storage. It explicitly distinguishes itself from the sibling uichemy_upload_image (which is for bytes you generated), so the agent can pick without opening either 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?

States the exact condition that selects this tool ('pictures you have ON DISK without retyping them as base64') versus the alternative ('uichemy_upload_image is the right tool for a picture you generated as bytes') and names the downstream tool to pass results to (uichemy_set_images).

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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