sickn33/agentic-awesome-skills/atlas-cloud-media
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Generate Atlas Cloud images and videos through its asynchronous media API with schema-first model selection and credential-safe polling.
Install
npx vskill@latest install sickn33/agentic-awesome-skills/atlas-cloud-mediaSKILL.md
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
Cloud.
- Use when an existing workflow needs an Atlas Cloud image or video generation
request and can make HTTPS calls.
- Use when model-specific parameters must be discovered before submission.
- Do not use this skill for OpenAI-compatible text chat; that API has a
different base URL and contract.
Preconditions
- Confirm the user is authorized to send the prompt and any reference media
to a third-party service.
- Explain that generation is paid and obtain approval before submitting a
billable request.
- Require
ATLASCLOUD_API_KEYto be present in the environment. Never ask the
user to paste it into chat, source files, command history, or logs.
- 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:
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
0. Create a Private Per-Run Workspace
Run the remaining shell snippets in the same shell session. Create a private directory before writing prompts, responses, prediction IDs, or signed URLs; the parameter expansion in later steps fails closed when this setup was skipped.
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:
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:
Video example using a catalog-confirmed model:
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 enforce a ten-minute wall-clock deadline in the host. The attempt cap below is not itself a ten-minute bound because HTTP request time also counts. Preserve the prediction ID for diagnostics, but never log request headers or the API key.
4. Download and Verify the Output
Read the first HTTPS URL from .data.outputs. Atlas output URLs are temporary, so download promptly. Validate each redirect host and resolved IP against approved public media destinations; HTTPS alone does not prevent access to local/private networks. 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.
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
401or403: stop and ask the user to verify access. Do not print or rotate
the key automatically.
400or422: fetch the model's current schema and correct the payload. Do
not blindly resubmit.
429: stop and report rate limiting; respect anyRetry-Aftervalue.5xxor network timeout: first poll a known prediction ID. Do not create a
second paid task unless the user approves the possible duplicate charge.
failedortimeout: report the sanitized service error and prediction ID;
do not claim an output was generated.
- Missing or invalid media: keep the original response for diagnosis, do not
overwrite an existing destination, and do not mark the task complete.
Best Practices
- Use the public catalog and per-model schema immediately before generation.
- Keep request and response artifacts in one private per-run directory and let
the exit trap remove them, especially prediction payloads with signed URLs.
- Submit one task at a time unless the user explicitly approves a batch and its
cost.
- Keep prompts, reference-media rights, and provider content policies visible
in the approval step.
- Use short polling intervals only while a task is active; always enforce a
deadline.
- 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
Atlas Cloud client, bundled script, queue worker, or retry service.
- Available models, schemas, prices, and output retention can change; the live
catalog is authoritative.
- 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
accuracy, rights, or safety.
Security & Safety Notes
- Treat prompts and uploaded media as data sent to a third party; obtain user
consent first and avoid unnecessary personal or confidential information.
- 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
hosting or unrelated file transfer.
- Follow applicable laws, provider policies, and intellectual-property rights.
Common Pitfalls
- Problem: A payload copied from another model returns a validation error.
Solution: Fetch the selected catalog entry's current schema and rebuild the request from that schema.
- Problem: A network timeout causes a duplicate paid request.
Solution: Preserve and poll the original prediction ID before considering a resubmission.
- Problem: The downloaded file is HTML or JSON instead of media.
Solution: Check the HTTP status, content type, file signature, and size before renaming or publishing it.
- Problem: Output download leaks the API key to another host.
Solution: Use a fresh download request with no Atlas authorization header.
Related Skills
@video-router- Decide whether a request should use generated video before
submitting a billable task.
@image-studio- Plan and review image-production work around generated
assets.
Security
- Security scanPassed, 100 of 100Pattern checks on the skill's files.
- Model reviewNot runA model review is scheduled for the next rescan.
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingskills/atlas-cloud-media/SKILL.md
Popularity
- Repository stars
- 47,054
- Repository forks
- 6,853
- 7-day trend score
- 54
Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.
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