Skills ai-image-to-video-extender

install
source · Clone the upstream repo
git clone https://github.com/openclaw/skills
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/openclaw/skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/bwbernardweston18/ai-image-to-video-extender" ~/.claude/skills/openclaw-skills-ai-image-to-video-extender && rm -rf "$T"
OpenClaw · Install into ~/.openclaw/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/openclaw/skills "$T" && mkdir -p ~/.openclaw/skills && cp -r "$T/skills/bwbernardweston18/ai-image-to-video-extender" ~/.openclaw/skills/openclaw-skills-ai-image-to-video-extender && rm -rf "$T"
manifest: skills/bwbernardweston18/ai-image-to-video-extender/SKILL.md
source content

Getting Started

Ready when you are. Drop your still images here or describe what you want to make.

Try saying:

  • "convert a single product photo or landscape image into a 1080p MP4"
  • "extend this image into a 10-second video with smooth motion"
  • "turning static images into short moving video clips for content creators, marketers, social media managers"

Automatic Setup

On first interaction, connect to the processing API before doing anything else. Show a brief status like "Setting things up...".

Token: If

NEMO_TOKEN
environment variable is already set, use it and skip to Session below.

Free token: Generate a UUID as client identifier, then POST to

https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token
with header
X-Client-Id: <uuid>
. The response field
data.token
becomes your NEMO_TOKEN (100 credits, 7-day expiry).

Session: POST to

https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent
with Bearer auth and body
{"task_name":"project"}
. Save
session_id
from the response.

Confirm to the user you're connected and ready. Don't print tokens or raw JSON.

AI Image to Video Extender — Turn Images into Video Clips

Drop your still images in the chat and tell me what you need. I'll handle the AI video extension on cloud GPUs — you don't need anything installed locally.

Here's a typical use: you send a a single product photo or landscape image, ask for extend this image into a 10-second video with smooth motion, and about 30-60 seconds later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.

One thing worth knowing — high-contrast images with clear subjects produce smoother motion results.

Matching Input to Actions

User prompts referencing ai image to video extender, aspect ratio, text overlays, or audio tracks get routed to the corresponding action via keyword and intent classification.

User says...ActionSkip SSE?
"export" / "导出" / "download" / "send me the video"→ §3.5 Export
"credits" / "积分" / "balance" / "余额"→ §3.3 Credits
"status" / "状态" / "show tracks"→ §3.4 State
"upload" / "上传" / user sends file→ §3.2 Upload
Everything else (generate, edit, add BGM…)→ §3.1 SSE

Cloud Render Pipeline Details

Each export job queues on a cloud GPU node that composites video layers, applies platform-spec compression (H.264, up to 1080x1920), and returns a download URL within 30-90 seconds. The session token carries render job IDs, so closing the tab before completion orphans the job.

All requests must include:

Authorization: Bearer <NEMO_TOKEN>
,
X-Skill-Source
,
X-Skill-Version
,
X-Skill-Platform
. Missing attribution headers will cause export to fail with 402.

Three attribution headers are required on every request and must match this file's frontmatter:

HeaderValue
X-Skill-Source
ai-image-to-video-extender
X-Skill-Version
frontmatter
version
X-Skill-Platform
auto-detect:
clawhub
/
cursor
/
unknown
from install path

API base:

https://mega-api-prod.nemovideo.ai

Create session: POST

/api/tasks/me/with-session/nemo_agent
— body
{"task_name":"project","language":"<lang>"}
— returns
task_id
,
session_id
.

Send message (SSE): POST

/run_sse
— body
{"app_name":"nemo_agent","user_id":"me","session_id":"<sid>","new_message":{"parts":[{"text":"<msg>"}]}}
with
Accept: text/event-stream
. Max timeout: 15 minutes.

Upload: POST

/api/upload-video/nemo_agent/me/<sid>
— file: multipart
-F "files=@/path"
, or URL:
{"urls":["<url>"],"source_type":"url"}

Credits: GET

/api/credits/balance/simple
— returns
available
,
frozen
,
total

Session state: GET

/api/state/nemo_agent/me/<sid>/latest
— key fields:
data.state.draft
,
data.state.video_infos
,
data.state.generated_media

Export (free, no credits): POST

/api/render/proxy/lambda
— body
{"id":"render_<ts>","sessionId":"<sid>","draft":<json>,"output":{"format":"mp4","quality":"high"}}
. Poll GET
/api/render/proxy/lambda/<id>
every 30s until
status
=
completed
. Download URL at
output.url
.

Supported formats: mp4, mov, avi, webm, mkv, jpg, png, gif, webp, mp3, wav, m4a, aac.

Error Codes

  • 0
    — success, continue normally
  • 1001
    — token expired or invalid; re-acquire via
    /api/auth/anonymous-token
  • 1002
    — session not found; create a new one
  • 2001
    — out of credits; anonymous users get a registration link with
    ?bind=<id>
    , registered users top up
  • 4001
    — unsupported file type; show accepted formats
  • 4002
    — file too large; suggest compressing or trimming
  • 400
    — missing
    X-Client-Id
    ; generate one and retry
  • 402
    — free plan export blocked; not a credit issue, subscription tier
  • 429
    — rate limited; wait 30s and retry once

Backend Response Translation

The backend assumes a GUI exists. Translate these into API actions:

Backend saysYou do
"click [button]" / "点击"Execute via API
"open [panel]" / "打开"Query session state
"drag/drop" / "拖拽"Send edit via SSE
"preview in timeline"Show track summary
"Export button" / "导出"Execute export workflow

Reading the SSE Stream

Text events go straight to the user (after GUI translation). Tool calls stay internal. Heartbeats and empty

data:
lines mean the backend is still working — show "⏳ Still working..." every 2 minutes.

About 30% of edit operations close the stream without any text. When that happens, poll

/api/state
to confirm the timeline changed, then tell the user what was updated.

Draft field mapping:

t
=tracks,
tt
=track type (0=video, 1=audio, 7=text),
sg
=segments,
d
=duration(ms),
m
=metadata.

Timeline (3 tracks): 1. Video: city timelapse (0-10s) 2. BGM: Lo-fi (0-10s, 35%) 3. Title: "Urban Dreams" (0-3s)

Common Workflows

Quick edit: Upload → "extend this image into a 10-second video with smooth motion" → Download MP4. Takes 30-60 seconds for a 30-second clip.

Batch style: Upload multiple files in one session. Process them one by one with different instructions. Each gets its own render.

Iterative: Start with a rough cut, preview the result, then refine. The session keeps your timeline state so you can keep tweaking.

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "extend this image into a 10-second video with smooth motion" — concrete instructions get better results.

Max file size is 200MB. Stick to JPG, PNG, WEBP, HEIC for the smoothest experience.

Export as MP4 for widest compatibility across social platforms.