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Upload image to Pool Pro Florida media library

upload_media

Import an image attached in ChatGPT into the Pool Pro Florida CMS media library. ChatGPT supplies a temporary download URL and file ID through its native file parameter handoff. The server downloads the image directly, validates it, strips embedded metadata by re-encoding to WebP, stores it outside Git, and returns a stable /media/... URL. This tool does not modify any page.

Input Schema

NameRequiredDescriptionDefault
altNoAccessible alt text for the image.
fileYes
tagsNoOptional media tags such as hero, riverview, or generated.
sourceNoWhether the image came from image generation or a user upload.
captionNoOptional media-library caption.
filenameNoOptional override filename. If omitted, the filename supplied by ChatGPT is used.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.1/5.0
Behavior4/5

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

Annotations only provide the generic readOnly/destructive/openWorld flags; the description adds real substance beyond them by disclosing the server-side pipeline: direct download, validation, metadata stripping via re-encoding to WebP, storage outside Git, and a returned stable /media/... URL. It stops short of covering failure modes, size limits, or auth requirements, so it is not exhaustive.

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 purpose, then the mechanics in one dense but information-bearing sentence, closing with a scope constraint. Four sentences with essentially no filler, though the middle sentence is packed enough to be slightly heavy.

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

Completeness4/5

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

With no output schema, the description usefully explains that the tool returns a stable /media/... URL, and with 6 parameters and a nested file object it explains how that nested input arrives. It omits error behavior, limits, and what validation actually accepts, but is adequate for correct invocation.

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 coverage is 83%, so the schema already documents alt, tags, source, caption, filename, and the nested file fields. The description only reinforces the file handoff concept (temporary download URL + file ID) and adds no new meaning for the other parameters, so the baseline 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?

States a concrete verb and resource ('Import an image ... into the Pool Pro Florida CMS media library') plus the source of the input (an image attached in ChatGPT via its native file handoff). No sibling tool touches media, and the description makes that domain obvious 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 Guidelines4/5

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

It clearly signals the triggering situation: an image attached in ChatGPT that needs to land in the CMS, with the file arriving through the native file parameter handoff. It also clarifies the boundary 'This tool does not modify any page,' but gives no explicit exclusions or alternative tools, so it stops short of full when/when-not routing.

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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