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agent-media

Upload images

open_upload_panel

Open a drag-and-drop image upload panel for the user. Use when the user wants to supply photos, portraits, products, or image references, especially in Claude or ChatGPT. PNG/JPEG/WebP, up to 25 MB each and 10 images, available for up to 24 hours. No generation credits. Returns a browser link for clients without inline panels. Never ask the user to paste base64. After the user uploads, call get_uploads with the returned session_id; use the exact image_url in refs, first_frame, or a skill image field. Do not generate before images are ready.

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior4/5

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

Adds substantial context beyond the sparse annotations: accepted formats, 25 MB per-file and 10-image limits, 24-hour retention, no credit consumption, and a browser-link fallback for clients lacking inline panels. Missing only failure behavior (what happens if the panel is unavailable or the session expires mid-upload).

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 action, then constraints, then follow-up instructions — every sentence carries operational content. It is slightly dense, packing limits, cost, fallback, and chaining rules into one block, but nothing is filler.

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?

With no input schema and no output schema, the description must carry the full contract, and it does: trigger condition, limits, lifetime, cost, return channels, and the exact next tool call. An agent can act correctly without any other information.

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?

Zero parameters, so the baseline is 4; the schema is a closed empty object. The description instead documents the outputs (session_id, image_url) and where to place them (refs, first_frame, skill image field), which is valuable but is return-value guidance rather than parameter semantics.

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 action (open a drag-and-drop image upload panel) and its resource (images), plus the user-facing intent (supply photos, portraits, products). It is clearly distinguishable from siblings like upload_image (direct upload) and get_uploads (retrieval after upload).

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 (user wants to supply image references), explicit anti-pattern ('Never ask the user to paste base64'), and an explicit next step ('After the user uploads, call get_uploads'). It also warns not to generate before images are ready, which routes the agent correctly relative to generate_image.

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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