Install the "atlas-cloud-media" agent skill from https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/atlas-cloud-media into .claude/skills/atlas-cloud-media/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "atlas-cloud-media", then confirm the skill loads.
Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
skills CLI
$ npx skills add sickn33/agentic-awesome-skills --skill atlas-cloud-media -a codex
Project install goes to .agents/skills/; add -g for ~/.codex/skills/.
Install the "atlas-cloud-media" agent skill from https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/atlas-cloud-media into .agents/skills/atlas-cloud-media/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "atlas-cloud-media", then confirm the skill loads.
Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
skills CLI
$ npx skills add sickn33/agentic-awesome-skills --skill atlas-cloud-media -a cursor
Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.
Install the "atlas-cloud-media" agent skill from https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/atlas-cloud-media into .cursor/skills/atlas-cloud-media/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "atlas-cloud-media", then confirm the skill loads.
Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
skills CLI
$ npx skills add sickn33/agentic-awesome-skills --skill atlas-cloud-media -a gemini-cli
Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.
Install the "atlas-cloud-media" agent skill from https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/atlas-cloud-media into .gemini/skills/atlas-cloud-media/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "atlas-cloud-media", then confirm the skill loads.
Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
skills CLI
$ npx skills add sickn33/agentic-awesome-skills --skill atlas-cloud-media -a github-copilot
Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.
Install the "atlas-cloud-media" agent skill from https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/atlas-cloud-media into .github/skills/atlas-cloud-media/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "atlas-cloud-media", then confirm the skill loads.
GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
skills CLI
$ npx skills add sickn33/agentic-awesome-skills --skill atlas-cloud-media -a opencode
OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
Install the "atlas-cloud-media" agent skill from https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/atlas-cloud-media into .opencode/skills/atlas-cloud-media/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "atlas-cloud-media", then confirm the skill loads.
OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
Skill name
atlas-cloud-media
GitHub stars
47k
Used in
1 other repo
Token cost
~2.8k tokens
SKILL.md length
1,019 words
Files
1
Skills in repo
1,497
Repo updated
First seen
Licence
MIT
At a glance
Generate Atlas Cloud images and videos through its asynchronous media API with schema-first model selection and credential-safe polling.
Works in 5 steps: Create a Private Per-Run Workspace → Discover and Validate a Model → Submit One Generation Task → …
Tasks that involve Async programming
SKILL.md covers Overview, When to Use This Skill, Preconditions and API Contract, plus 7 more sections
Calls jq and curl; reaches api.atlascloud.ai; needs ATLASCLOUD_API_KEY
What it does
Atlas Cloud Media is an agent skill from sickn33/agentic-awesome-skills. Generate Atlas Cloud images and videos through its asynchronous media API with schema-first model selection and credential-safe polling.
Its SKILL.md is about 2.8k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Media & Creative, covering Async programming. The repository describes itself as: AAS Core is the local, agent-first control plane for complete catalog discovery, agent-owned selection, stack validation, and planning, backed by 2,400+ agentic skills. Includes… The licence is MIT.
When your agent uses it
Tasks that involve Async programming
Example prompts
“/atlas-cloud-media”
Requirements
A credential in ATLASCLOUD_API_KEY
Workflow steps
5 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit b84d35a. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
jq
curl
From the folder's file list and the shell code blocks in SKILL.md.
Network
Hosts in commands or code, which the agent is likely to contact:
api.atlascloud.ai
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names these keys or tokens, usually read from environment variables:
ATLASCLOUD_API_KEY
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Atlas Cloud Media loads about 2.8k tokens when it runs. Until then it costs about 39 tokens; SKILL.md has 1,019 words of instructions outside code blocks.
Always· name and description, kept in context so the agent knows when to use it
~39
When it runs· the whole SKILL.md, loaded when a task matches
~2.8k
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
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_KEY to 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.
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.
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.
bash
prediction_id=$(jq -er '.data.id | select(type == "string" and length > 0)' \
"${atlas_tmp_dir:?run private workspace setup first}/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 $ATLASCLOUD_API_KEY" \
--output "$atlas_tmp_dir/prediction.json"
status=$(jq -r '.data.status // "unknown"' "$atlas_tmp_dir/prediction.json")
case "$status" in
completed|succeeded) break ;;
failed|timeout)
jq -r '.data.error // "Atlas Cloud generation failed"' \
"$atlas_tmp_dir/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.
bash
output_url=$(jq -er '.data.outputs[0] | select(startswith("https://"))' \
"${atlas_tmp_dir:?run private workspace setup first}/prediction.json")
curl --fail --silent --show-error --location \
"$output_url" \
--output "$atlas_tmp_dir/output.bin"
test -s "$atlas_tmp_dir/output.bin"
file "$atlas_tmp_dir/output.bin"
# ATLAS_OUTPUT_DIR must be the user-approved destination. Resolve it to a
# physical directory, copy into an exclusive same-directory temporary file,
# then create the final name with one atomic hard-link operation. `ln` fails if
# any target already exists, including a dangling symlink.
atlas_output_dir=$(cd -- "${ATLAS_OUTPUT_DIR:?set the approved output directory}" && pwd -P) || exit 1
atlas_output_path="$atlas_output_dir/atlas-output.bin"
if ! (
set -eu
umask 077
atlas_publish_tmp=$(mktemp "$atlas_output_dir/.atlas-output.XXXXXXXX")
trap 'rm -f -- "$atlas_publish_tmp"' EXIT
cp -- "$atlas_tmp_dir/output.bin" "$atlas_publish_tmp"
chmod 644 -- "$atlas_publish_tmp"
ln -- "$atlas_publish_tmp" "$atlas_output_path"
); then
printf '%s\n' "Refusing to overwrite or redirect $atlas_output_path" >&2
exit 1
fi
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
the key automatically.
400 or 422: fetch the model's current schema and correct the payload. Do
not blindly resubmit.
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
second paid task unless the user approves the possible duplicate charge.
failed or timeout: 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.
Show full SKILL.md (363 more words)Show less
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.
We found 5 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in sickn33/agentic-awesome-skills, which our catalogue first saw on October 7, 2026.
Atlas Cloud Media next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
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Generate Atlas Cloud images and videos through its asynchronous media API with schema-first model selection and credential-safe polling. Atlas Cloud Media is an agent skill from sickn33/agentic-awesome-skills. Generate Atlas Cloud images and videos through its asynchronous media API with schema-first model selection and credential-safe polling.
When should I use Atlas Cloud Media?
Atlas Cloud Media fits situations like: tasks that involve Async programming.
How do I install Atlas Cloud Media in Claude Code?
Run `npx skills add sickn33/agentic-awesome-skills --skill atlas-cloud-media -a claude-code`. Or copy the skill folder (skills/atlas-cloud-media in sickn33/agentic-awesome-skills) into .claude/skills/atlas-cloud-media in your project. Claude Code loads it when a task matches its description.
How do I install Atlas Cloud Media in Codex?
Run `npx skills add sickn33/agentic-awesome-skills --skill atlas-cloud-media -a codex`. Or copy the skill folder (skills/atlas-cloud-media in sickn33/agentic-awesome-skills) into .agents/skills/atlas-cloud-media in your project. Codex loads it when a task matches its description.
Can I use Atlas Cloud Media in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add sickn33/agentic-awesome-skills --skill atlas-cloud-media -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/atlas-cloud-media, .gemini/skills/atlas-cloud-media, .github/skills/atlas-cloud-media and .opencode/skills/atlas-cloud-media in your project.
What does Atlas Cloud Media need to run?
Going by SKILL.md and its folder, Atlas Cloud Media needs the command-line tools its instructions call (jq and curl) and credentials named ATLASCLOUD_API_KEY. Our summary lists: A credential in ATLASCLOUD_API_KEY.
Does Atlas Cloud Media access the network?
SKILL.md names 1 domain. In commands or code: api.atlascloud.ai; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.
Is Atlas Cloud Media safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Atlas Cloud Media use?
Atlas Cloud Media is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Atlas Cloud Media use?
About 2.8k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Atlas Cloud Media?
Skills that share tags, products or a category with Atlas Cloud Media: Dsh CI Test Reliability (Zhou-Yujing114514/deepseek-harness-linux, 120 stars), Image Generation Gateways (calesthio/generative-media-skills, 197 stars), Stable Audio (calesthio/generative-media-skills, 197 stars) and YugabyteDB ASH Instrumentation (yugabyte/yugabyte-db, 11k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Atlas Cloud Media?
sickn33 (a GitHub user) maintains it in sickn33/agentic-awesome-skills, which has 47,405 GitHub stars. The repository holds 1,497 skills in this directory. The repository was last updated on October 9, 2026.