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Atlas Cloud Media

CommunityPopular
davepoon
atlas-cloud-media

Discover Atlas Cloud image and video models, inspect their live schemas, and submit one confirmed media generation request with bounded GET polling. Use when integrating Atlas Cloud media APIs or generating images and videos without hard-coding stale model parameters.

Overview

Publisherdavepoon
Repositorybuildwithclaude
Skill nameatlas-cloud-media
Stars
3.5K
Forks
509
Bundled files
2
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by davepoon on GitHub. Read the source before you install it.

Installation

Install the Atlas Cloud Media AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/davepoon/buildwithclaude.git /tmp/buildwithclaude
mkdir -p .claude/skills
cp -r /tmp/buildwithclaude/plugins/all-skills/skills/atlas-cloud-media .claude/skills/atlas-cloud-media
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Atlas Cloud Media in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Atlas Cloud Media on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Atlas Cloud Media is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Atlas Cloud Media

Use the bundled scripts/atlas_media.py CLI to discover current Atlas Cloud models, inspect a model's live request schema, and run asynchronous image or video generation.

When to Use This Skill

  • The user wants to find an available Atlas Cloud image or video model.
  • An integration needs the current model ID, input fields, endpoint, or price.
  • The user wants one explicitly confirmed media generation request.
  • An asynchronous Atlas Cloud task needs bounded status polling.

Setup

Set the API key in the environment. Never pass it as a CLI argument or commit it to a repository.

bash
export ATLASCLOUD_API_KEY="your-api-key"

ATLASCLOUD_BASE_URL may point to a compatible deployment. It defaults to https://api.atlascloud.ai.

Workflow

1. Discover current models

bash
python3 scripts/atlas_media.py models --type Image --query flux
python3 scripts/atlas_media.py models --type Video --query seedance

Treat model availability and prices as live data. Run discovery immediately before choosing a model.

2. Inspect the exact schema

bash
python3 scripts/atlas_media.py describe black-forest-labs/flux-schnell

The command resolves the model's current schema URL and reports the required fields, property definitions, submission endpoint, result endpoint, and catalog price data. Build the payload from this output instead of copying an old example.

3. Prepare parameters in a file

json
{
  "prompt": "A clean product photograph on a neutral background",
  "size": "1024*1024",
  "num_images": 1
}

Do not include model; the CLI inserts the selected model ID after validation.

4. Confirm cost and generate once

bash
python3 scripts/atlas_media.py generate \
  black-forest-labs/flux-schnell \
  --params-file request.json \
  --confirm-paid

The --confirm-paid flag is mandatory. The CLI sends exactly one generation POST and does not retry it. It polls only the schema-defined GET result endpoint, with a fixed interval and maximum poll count.

Use stdin when a temporary file is unnecessary:

bash
printf '%s' '{"prompt":"A geometric app icon"}' | \
  python3 scripts/atlas_media.py generate \
    black-forest-labs/flux-schnell \
    --params-file - \
    --confirm-paid

Safety Rules

  • Keep ATLASCLOUD_API_KEY server-side and out of logs, prompts, screenshots, browser code, mobile apps, and committed files.
  • Never retry a generation POST automatically. If submission fails, report the error and require a new explicit confirmation before another paid request.
  • Poll only with GET and stop at --max-polls.
  • Validate the live schema again when changing models.
  • Download returned media URLs before they expire when persistent storage is required.
  • Require human review for sensitive, regulated, or high-impact content.

Output

Commands write structured JSON to stdout. Successful generation output includes the prediction ID, final status, generated URLs, model ID, and the endpoints resolved from the live schema.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Atlas Cloud Media AI skill do?

Discover Atlas Cloud image and video models, inspect their live schemas, and submit one confirmed media generation request with bounded GET polling. Use when integrating Atlas Cloud media APIs or generating images and videos without hard-coding stale model parameters.

Why use Atlas Cloud Media on TypingMind?

Because you install it once and use it with any model. Atlas Cloud Media is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Atlas Cloud Media in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/davepoon/buildwithclaude/tree/main/plugins/all-skills/skills/atlas-cloud-media. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Atlas Cloud Media?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Atlas Cloud Media?

As many as you like. As long as a model supports skills, you can use Atlas Cloud Media with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Atlas Cloud Media AI skill free?

Yes. It is published on GitHub by davepoon under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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