Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add aAAaqwq/AGI-Super-Team --skill atlas-video-gengit clone --depth 1 https://github.com/aAAaqwq/AGI-Super-TeamWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/aaaaqwq/agi-super-team/atlas-video-gen)<a href="https://agentmods.dev/skills/aaaaqwq/agi-super-team/atlas-video-gen"><img src="https://agentmods.dev/badge/skills/aaaaqwq/agi-super-team/atlas-video-gen/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/aaaaqwq/agi-super-team/atlas-video-gen"><img src="https://agentmods.dev/badge/skills/aaaaqwq/agi-super-team/atlas-video-gen.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00042 | $0.00855 |
| Opus 5.5 | $0.00017 | $0.00342 |
| Sonnet 5.5 | $0.00008 | $0.00171 |
| Haiku 4.5 | $0.00004 | $0.00085 |
Grade A, and why
atlas-video-gen scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Atlas Cloud Video Generation
Generate one text-to-video clip with Atlas Cloud's google/veo3.1-lite/text-to-video
model. This is an opt-in workflow and does not replace any other video provider.
Prerequisites
- Python 3.10 or newer; the helper uses only the standard library.
- An Atlas Cloud API key in
ATLASCLOUD_API_KEY. - Outbound HTTPS access to
api.atlascloud.aiand the returned output URL.
Set the key in the environment. Never put it in a prompt, command argument, source file, or log.
export ATLASCLOUD_API_KEY="..."
Safety Boundary
Running a generation request may incur charges. The helper prints the exact
request plan and exits without network access unless --yes is present.
The generation POST is sent exactly once and is never retried. Only prediction
and output GET requests use bounded retries for transient failures. If the
submission result is unclear, stop and inspect the Atlas Cloud console instead
of running the command again.
Usage
Preview the request first:
python skills/atlas-video-gen/scripts/generate_video.py \
"A slow aerial orbit around a lighthouse at sunrise" \
--output lighthouse.mp4
After reviewing the plan, confirm one paid submission:
python skills/atlas-video-gen/scripts/generate_video.py \
"A slow aerial orbit around a lighthouse at sunrise" \
--output lighthouse.mp4 \
--duration 4 \
--ratio 16:9 \
--resolution 720p \
--yes
Use --json for a machine-readable result. The default timeout is 10 minutes,
and --poll-interval controls prediction polling frequency.
Supported Inputs
| Option | Values | Default |
|---|---|---|
--duration |
4, 6, 8 |
8 |
--ratio |
16:9, 9:16 |
16:9 |
--resolution |
720p, 1080p |
720p |
--seed |
integer; -1 requests a random seed |
-1 |
Atlas Cloud's current schema requires an 8-second duration for 1080p output.
The helper validates that rule before submitting.
Workflow
- Turn the request into a concise English video prompt with subject motion, camera movement, setting, lighting, and audio cues when relevant.
- Preview the helper command without
--yes. - Obtain explicit human approval for the displayed model and parameters.
- Run once with
--yes. - Wait for terminal prediction status and report the saved MP4 path.
- On an ambiguous submission or failure, do not resubmit automatically.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 106 lines · 42 tokens per session scan A f8abac667cdd
atlas-video-gen is a skill published in the GitHub repository aAAaqwq/AGI-Super-Team (110 stars, last pushed yesterday), licensed MIT. It adds 42 tokens to every session and 855 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-07.
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