Skills create-video-using-ai
git clone https://github.com/openclaw/skills
T=$(mktemp -d) && git clone --depth=1 https://github.com/openclaw/skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/bwbernardweston18/create-video-using-ai" ~/.claude/skills/clawdbot-skills-create-video-using-ai && rm -rf "$T"
skills/bwbernardweston18/create-video-using-ai/SKILL.mdGetting Started
Share your images or clips and I'll get started on AI video creation. Or just tell me what you're thinking.
Try saying:
- "create my images or clips"
- "export 1080p MP4"
- "turn these photos into a 30-second"
First-Time Connection
When a user first opens this skill, connect to the processing backend automatically. Briefly let them know (e.g. "Setting up...").
Authentication: Check if
NEMO_TOKEN is set in the environment. If it is, skip to step 2.
- Obtain a free token: Generate a random UUID as client identifier. POST to
with headerhttps://mega-api-prod.nemovideo.ai/api/auth/anonymous-token
set to that UUID. The responseX-Client-Id
is your NEMO_TOKEN — 100 free credits, valid 7 days.data.token - Create a session: POST to
withhttps://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent
,Authorization: Bearer <token>
, and bodyContent-Type: application/json
. Store the returned{"task_name":"project","language":"<detected>"}
for all subsequent requests.session_id
Keep setup communication brief. Don't display raw API responses or token values to the user.
Create Video Using AI — Generate Videos from Your Assets
Drop your images or clips in the chat and tell me what you need. I'll handle the AI video creation on cloud GPUs — you don't need anything installed locally.
Here's a typical use: you send a five product photos and a logo file, ask for turn these photos into a 30-second promotional video with music and transitions, and about 1-2 minutes later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.
One thing worth knowing — using fewer than 10 images keeps generation time under a minute.
Matching Input to Actions
User prompts referencing create video using ai, aspect ratio, text overlays, or audio tracks get routed to the corresponding action via keyword and intent classification.
| User says... | Action | Skip 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.
Headers are derived from this file's YAML frontmatter.
X-Skill-Source is create-video-using-ai, X-Skill-Version comes from the version field, and X-Skill-Platform is detected from the install path (~/.clawhub/ = clawhub, ~/.cursor/skills/ = cursor, otherwise unknown).
Include
Authorization: Bearer <NEMO_TOKEN> and all attribution headers on every request — omitting them triggers a 402 on export.
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.
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.
Translating GUI Instructions
The backend responds as if there's a visual interface. Map its instructions to API calls:
- "click" or "点击" → execute the action via the relevant endpoint
- "open" or "打开" → query session state to get the data
- "drag/drop" or "拖拽" → send the edit command through SSE
- "preview in timeline" → show a text summary of current tracks
- "Export" or "导出" → run the export workflow
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)
Error Codes
— success, continue normally0
— token expired or invalid; re-acquire via1001/api/auth/anonymous-token
— session not found; create a new one1002
— out of credits; anonymous users get a registration link with2001
, registered users top up?bind=<id>
— unsupported file type; show accepted formats4001
— file too large; suggest compressing or trimming4002
— missing400
; generate one and retryX-Client-Id
— free plan export blocked; not a credit issue, subscription tier402
— rate limited; wait 30s and retry once429
Common Workflows
Quick edit: Upload → "turn these photos into a 30-second promotional video with music and transitions" → Download MP4. Takes 1-2 minutes 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 "turn these photos into a 30-second promotional video with music and transitions" — concrete instructions get better results.
Max file size is 500MB. Stick to MP4, MOV, JPG, PNG for the smoothest experience.
Export as MP4 for widest compatibility across platforms.