atlas-cloud-media

Atlas Cloud Media

Overview

Use Atlas Cloud's asynchronous media API to generate images or videos. This
source-only skill describes model discovery, schema validation, task
submission, bounded polling, and safe output retrieval; it does not bundle an
SDK, executable, or hosted runtime.

When to Use This Skill

• Use when the user explicitly asks to generate an image or video with Atlas

• Use when an existing workflow needs an Atlas Cloud image or video generation

• Use when model-specific parameters must be discovered before submission.

• Do not use this skill for OpenAI-compatible text chat; that API has a

Preconditions

1. Confirm the user is authorized to send the prompt and any reference media
to a third-party service.
2. Explain that generation is paid and obtain approval before submitting a
billable request.
3. Require ATLASCLOUD_API_KEY to be present in the environment. Never ask the
user to paste it into chat, source files, command history, or logs.
4. Confirm the output directory and whether the user wants image generation,
video generation, or both.

API Contract

| Operation | Method and endpoint |
| --- | --- |
| List models | GET https://api.atlascloud.ai/api/v1/models |
| Generate image | POST https://api.atlascloud.ai/api/v1/model/generateImage |
| Generate video | POST https://api.atlascloud.ai/api/v1/model/generateVideo |
| Poll task | GET https://api.atlascloud.ai/api/v1/model/prediction/{id} |

Generation and polling requests use these headers:

Authorization: Bearer $ATLASCLOUD_API_KEY
Content-Type: application/json

The model catalog is public. Each catalog entry includes a schema URL; fetch
that schema and validate parameters against it before sending a paid request.
Do not guess parameters from another model, because names such as size,
ratio, aspect_ratio, image, and image_url are model-specific.

Workflow

1. Discover and Validate a Model

Fetch the catalog, filter by type (Image or Video), and match the user's
requested capability. Read the selected entry's schema, verify that all
required fields are present, and show the model and billable action to the user
before submission.

Example discovery request:

curl --fail --silent --show-error \
  "https://api.atlascloud.ai/api/v1/models" \
  --output /tmp/atlas-models.json
jq -r '.data[] | select(.type == "Image") | [.model, .displayName, .schema] | @tsv' \
  /tmp/atlas-models.json

2. Submit One Generation Task

Build the JSON body in a file so that quoting is deterministic and request
details can be reviewed without exposing the API key.

Image example using a catalog-confirmed model:

jq -n \
  --arg model "qwen-image-3.0/text-to-image" \
  --arg prompt "A paper-cut city map in blue and white, clean editorial style" \
  '{model: $model, prompt: $prompt, size: "1024*1024", n: 1}' \
  > /tmp/atlas-image-request.json
curl --fail --silent --show-error \
  --request POST \
  "https://api.atlascloud.ai/api/v1/model/generateImage" \
  --header "Authorization: Bearer $ATLASCLOUD_API_KEY" \
  --header "Content-Type: application/json" \
  --data @/tmp/atlas-image-request.json \
  --output /tmp/atlas-submit.json

Video example using a catalog-confirmed model:

jq -n \
  --arg model "bytedance/seedance-2.0-fast/text-to-video" \
  --arg prompt "A small paper boat crossing a calm pond, locked camera" \
  '{
    model: $model,
    prompt: $prompt,
    duration: 4,
    resolution: "480p",
    ratio: "16:9",
    generate_audio: false,
    watermark: false
  }' > /tmp/atlas-video-request.json
curl --fail --silent --show-error \
  --request POST \
  "https://api.atlascloud.ai/api/v1/model/generateVideo" \
  --header "Authorization: Bearer $ATLASCLOUD_API_KEY" \
  --header "Content-Type: application/json" \
  --data @/tmp/atlas-video-request.json \
  --output /tmp/atlas-submit.json

Check that .data.id is a non-empty string before polling. Treat a non-2xx
response or a missing ID as submission failure; do not retry a billable request
automatically because the original task may still have been accepted.

3. Poll with a Deadline

Poll every three seconds. Accept completed or succeeded as success, stop on
failed or timeout, and stop after ten minutes. Preserve the prediction ID
for diagnostics, but never log request headers or the API key.

prediction_id=$(jq -er '.data.id | select(type == "string" and length > 0)' \
  /tmp/atlas-submit.json)
for attempt in $(seq 1 200); do
  sleep 3
  curl --fail --silent --show-error \
    "https://api.atlascloud.ai/api/v1/model/prediction/$prediction_id" \
    --header "Authorization: Bearer $ATLASCLOUD_API_KEY" \
    --output /tmp/atlas-prediction.json
status=$(jq -r '.data.status // "unknown"' /tmp/atlas-prediction.json)
  case "$status" in
    completed|succeeded) break ;;
    failed|timeout)
      jq -r '.data.error // "Atlas Cloud generation failed"' \
        /tmp/atlas-prediction.json >&2
      exit 1
      ;;
  esac
done
test "$status" = "completed" || test "$status" = "succeeded"

4. Download and Verify the Output

Read the first HTTPS URL from .data.outputs. Atlas output URLs are temporary,
so download promptly. Do not send Authorization or any other Atlas request
headers to the output host. Reject non-HTTPS URLs and inspect the downloaded
file's content type and size before treating it as a valid deliverable.

output_url=$(jq -er '.data.outputs[0] | select(startswith("https://"))' \
  /tmp/atlas-prediction.json)
curl --fail --silent --show-error --location \
  "$output_url" \
  --output ./atlas-output.bin
test -s ./atlas-output.bin
file ./atlas-output.bin

Rename the file only after its detected type is known. Report the local path,
model ID, dimensions or duration, and whether the output passed basic playback
or decode validation.

Failure Handling

• 401 or 403: stop and ask the user to verify access. Do not print or rotate

• 400 or 422: fetch the model's current schema and correct the payload. Do

• 429: stop and report rate limiting; respect any Retry-After value.

• 5xx or network timeout: first poll a known prediction ID. Do not create a

• failed or timeout: report the sanitized service error and prediction ID;

• Missing or invalid media: keep the original response for diagnosis, do not

Best Practices

• Use the public catalog and per-model schema immediately before generation.

• Submit one task at a time unless the user explicitly approves a batch and its

• Keep prompts, reference-media rights, and provider content policies visible

• Use short polling intervals only while a task is active; always enforce a

• Download expiring outputs promptly and validate them locally.

• Never forward the Atlas bearer token to CDN or user-supplied URLs.

Limitations

• This source-only skill provides operational instructions, not an installed

• Available models, schemas, prices, and output retention can change; the live

• Model availability does not guarantee a prompt or reference asset is allowed.

• Generation is asynchronous and may take several minutes.

• Basic file checks do not replace human review of media quality, factual

Security & Safety Notes

• Treat prompts and uploaded media as data sent to a third party; obtain user

• Keep credentials in environment variables or an approved secret manager.

• Redact authorization headers and signed output URLs from logs and bug reports.

• Never execute downloaded media as code, and never use this workflow for bulk

• Follow applicable laws, provider policies, and intellectual-property rights.

Common Pitfalls

• Problem: A payload copied from another model returns a validation error.

• Problem: A network timeout causes a duplicate paid request.

• Problem: The downloaded file is HTML or JSON instead of media.

• Problem: Output download leaks the API key to another host.

Related Skills

• @video-router - Decide whether a request should use generated video before

• @image-studio - Plan and review image-production work around generated