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Video Openapi

v1.0.0

Turn a 2-minute MP4 product demo into 1080p processed video files just by typing what you need. Whether it's integrating video editing into apps via API call...

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Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for susan4731-wilfordf/video-openapi.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Video Openapi" (susan4731-wilfordf/video-openapi) from ClawHub.
Skill page: https://clawhub.ai/susan4731-wilfordf/video-openapi
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Required env vars: NEMO_TOKEN
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

Bare skill slug

openclaw skills install video-openapi

ClawHub CLI

Package manager switcher

npx clawhub@latest install video-openapi
Security Scan
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Benign
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OpenClawOpenClaw
Suspicious
medium confidence
Purpose & Capability
The name/description (remote video processing via API) match the declared need for a service token (NEMO_TOKEN) and the SKILL.md describes appropriate API endpoints for session creation, upload, SSE, and export. Requiring an API token is proportionate to the stated purpose.
Instruction Scope
SKILL.md instructs the agent to create sessions, upload user-provided files (multipart or URL), open SSE streams, poll state, and return download URLs — all expected for a remote render service. It does not ask the agent to read unrelated system files or environment variables. It also instructs the agent to hide technical details from the chat. However, the skill expects access to upload local files (user-supplied) and to call an anonymous-token endpoint if no token is present — worth noting for privacy.
Install Mechanism
Instruction-only skill with no install spec and no code files; nothing is written to disk by an installer. This is low install risk.
!
Credentials
The skill declares a single primary credential (NEMO_TOKEN), which is proportionate. However, the SKILL.md frontmatter includes a config path (~/.config/nemovideo/) while the registry metadata listed no required config paths — an inconsistency. Also the skill will create/obtain an anonymous token if NEMO_TOKEN is absent, meaning it will make network calls to mint tokens and then use those tokens for uploads; users should understand what data that token covers and whether it persists.
Persistence & Privilege
always:false and normal autonomous invocation are used. The skill does not request persistent system-level privileges nor modify other skills. No unusual persistence is requested.
What to consider before installing
This skill appears to do what it says (upload your videos to a remote render service using NEMO_TOKEN or a minted anonymous token). Before installing or using it: - Only upload videos you are comfortable sharing with an external service; rendered files and original uploads go over the network to mega-api-prod.nemovideo.ai. - Prefer to supply your own NEMO_TOKEN from a trusted account rather than relying on an anonymously minted token; verify token scope and expiry. - Ask the publisher (or inspect docs) about retention, who can access uploaded media, and whether the anonymous-token endpoint stores any identifying info. - Note the SKILL.md frontmatter mentions a config path (~/.config/nemovideo/) but the registry metadata did not — confirm whether the skill will read that directory (it may store credentials/state there). - If you have sensitive content, test with a non-sensitive sample first. Given the unknown source/homepage and the metadata inconsistency, exercise caution; if the publisher can provide documentation or a privacy policy, review it and re-evaluate.

Like a lobster shell, security has layers — review code before you run it.

Runtime requirements

🎬 Clawdis
EnvNEMO_TOKEN
Primary envNEMO_TOKEN
latestvk97fvgzxte5m3dyazb81j5zf1s85psy5
30downloads
0stars
1versions
Updated 10h ago
v1.0.0
MIT-0

Getting Started

Send me your video clips and I'll handle the API video processing. Or just describe what you're after.

Try saying:

  • "process a 2-minute MP4 product demo into a 1080p MP4"
  • "send a video file via API and get back an edited, processed video automatically"
  • "integrating video editing into apps via API calls for developers and marketers"

Getting Connected

Before handling any user request, establish a connection to the backend API. Show a brief status like "Connecting...".

If NEMO_TOKEN is in the environment, use it directly and create a session. Otherwise, acquire a free starter token:

  • Generate a UUID as client identifier
  • POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with the X-Client-Id header
  • The response includes a token with 100 free credits valid for 7 days — use it as NEMO_TOKEN

Then create a session by POSTing to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer authorization and body {"task_name":"project","language":"en"}. The session_id in the response is needed for all following requests.

Tell the user you're ready. Keep the technical details out of the chat.

Video OpenAPI — Process and Export Videos via API

Send me your video clips and describe the result you want. The API video processing runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload a 2-minute MP4 product demo, type "send a video file via API and get back an edited, processed video automatically", and you'll get a 1080p MP4 back in roughly 30-90 seconds. All rendering happens server-side.

Worth noting: smaller files under 100MB get API responses significantly faster.

Matching Input to Actions

User prompts referencing video openapi, 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.

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

HeaderValue
X-Skill-Sourcevideo-openapi
X-Skill-Versionfrontmatter version
X-Skill-Platformauto-detect: clawhub / cursor / unknown from install path

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 Handling

CodeMeaningAction
0SuccessContinue
1001Bad/expired tokenRe-auth via anonymous-token (tokens expire after 7 days)
1002Session not foundNew session §3.0
2001No creditsAnonymous: show registration URL with ?bind=<id> (get <id> from create-session or state response when needed). Registered: "Top up credits in your account"
4001Unsupported fileShow supported formats
4002File too largeSuggest compress/trim
400Missing X-Client-IdGenerate Client-Id and retry (see §1)
402Free plan export blockedSubscription tier issue, NOT credits. "Register or upgrade your plan to unlock export."
429Rate limit (1 token/client/7 days)Retry in 30s once

Common Workflows

Quick edit: Upload → "send a video file via API and get back an edited, processed video automatically" → Download MP4. Takes 30-90 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 "send a video file via API and get back an edited, processed video automatically" — concrete instructions get better results.

Max file size is 500MB. Stick to MP4, MOV, AVI, WebM for the smoothest experience.

H.264 MP4 gives the best balance of quality and size for API transfers.

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