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create_media_drop

Create a human drop page so ChatGPT or Claude users can upload laptop files (up to 20 per link) without dashboard login. Returns drop_url (https://www.poster.ly/drop/). Send that URL to the user, wait, then call list_media. Accepts JPEG, PNG, GIF, WebP, MP4, MOV, WebM, and PDF up to 50MB (a PDF is for LinkedIn document posts); HEIC is not accepted. This is not the chat paperclip and not create_signed_upload.

Input Schema

NameRequiredDescriptionDefault
filenameNoOptional filename hint, e.g. launch-video.mp4
max_filesNo
workspace_idNoOptional. The workspace this acts in and whose plan pays (from whoami). Needed only when your connection can act in several workspaces.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / max_files / maximum
      Previous value: -10New value: +20
  2. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Annotations only declare it is a non-readonly, non-idempotent, open-world write. The description adds substantial context beyond that: the return format (drop_url with token template), the no-login auth model, file/count/size limits, accepted and rejected formats, and the required follow-up call. It does not contradict any annotation.

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 purpose, then return value, workflow, constraints, and exclusions in a tight sequence; every sentence carries information. It is dense, but nothing is padding, so it sits just below the ideal for readability.

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 output schema, the description correctly explains the return value (drop_url format) and the full end-to-end flow including the subsequent list_media call. An agent has everything needed to invoke and follow through.

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 67%, with filename and workspace_id already documented. The description compensates for the undocumented max_files by stating the 'up to 20 per link' limit, aligning with the schema's 1-20 bounds, but adds no further syntax or per-param detail.

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 ('Create a human drop page') and immediately clarifies the audience and mechanism ('so ChatGPT or Claude users can upload laptop files ... without dashboard login'). It distinguishes itself from siblings by name ('not create_signed_upload', 'not the chat paperclip'), so the agent can route correctly without opening other schemas.

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 prescribes the workflow: create the drop, send the URL to the user, wait, then call list_media. It also names the alternatives it is not (chat paperclip, create_signed_upload), giving clear when/when-not guidance.

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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