Video Editing With Openclaw

v1.0.0

Skip the learning curve of professional editing software. Describe what you want — cut the silent pauses, add transitions, and export a clean final cut — and...

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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 linmillsd7/video-editing-with-openclaw.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Video Editing With Openclaw" (linmillsd7/video-editing-with-openclaw) from ClawHub.
Skill page: https://clawhub.ai/linmillsd7/video-editing-with-openclaw
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-editing-with-openclaw

ClawHub CLI

Package manager switcher

npx clawhub@latest install video-editing-with-openclaw
Security Scan
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medium confidence
Purpose & Capability
The skill advertises cloud AI video editing and only requests a single service credential (NEMO_TOKEN), which is appropriate for this purpose. However, SKILL.md frontmatter includes a config path (~/.config/nemovideo/) that is not listed in the registry metadata's required config paths — this mismatch should be clarified.
Instruction Scope
Instructions are focused on uploading video, session creation, SSE editing, and export flows to nemovideo.ai (expected). They also instruct obtaining an anonymous token via an external POST if NEMO_TOKEN is absent. The doc asks to 'auto-detect' platform from install path which could imply reading environment/paths; this is vague and may cause the agent to inspect install/runtime paths unnecessarily. All network calls target the stated nemovideo domain (no unrelated exfiltration endpoints described).
Install Mechanism
Instruction-only skill with no install spec and no code files present — nothing is written to disk by an installer, which is the lowest-risk installation model.
Credentials
Only NEMO_TOKEN is declared as required (primaryEnv), which fits a cloud API client. The frontmatter's mention of a config path (~/.config/nemovideo/) is inconsistent with registry metadata and could imply additional local config access; clarify whether the skill will read that path. The skill's instructions to create an anonymous token if none exists means it can obtain credentials itself — acceptable but worth noting.
Persistence & Privilege
The skill is not force-installed (always: false) and does not request any elevated or persistent platform privileges. Autonomous invocation is allowed (default) but not combined with broad or unrelated credential access.
Assessment
This skill appears to do what it says: upload your video to nemovideo.ai, create a session, and return edited output. Before installing, confirm you are comfortable uploading your videos to the mega-api-prod.nemovideo.ai domain and that you understand their retention/privacy policy. Ask the publisher to clarify the frontmatter/registry mismatch about ~/.config/nemovideo/ (is the skill going to read local config?). If you don't already have a NEMO_TOKEN, the skill will request an anonymous token on your behalf — test with non-sensitive/sample footage first, and be prepared to revoke the token/anonymous account when done. Finally, verify the skill will not try to access other environment variables or local files beyond the described flow.

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

Runtime requirements

🎬 Clawdis
EnvNEMO_TOKEN
Primary envNEMO_TOKEN
latestvk9751apg065xz5j81zb341qhmh858m92
92downloads
0stars
1versions
Updated 6d ago
v1.0.0
MIT-0

Getting Started

Share your raw video footage and I'll get started on AI-assisted video editing. Or just tell me what you're thinking.

Try saying:

  • "edit my raw video footage"
  • "export 1080p MP4"
  • "cut the silent pauses, add transitions,"

Quick Start Setup

This skill connects to a cloud processing backend. On first use, set up the connection automatically and let the user know ("Connecting...").

Token check: Look for NEMO_TOKEN in the environment. If found, skip to session creation. Otherwise:

  • Generate a UUID as client identifier
  • POST https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with X-Client-Id header
  • Extract data.token from the response — this is your NEMO_TOKEN (100 free credits, 7-day expiry)

Session: POST https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Keep the returned session_id for all operations.

Let the user know with a brief "Ready!" when setup is complete. Don't expose tokens or raw API output.

Video Editing with OpenClaw — Edit and Export Polished Videos

Drop your raw video footage in the chat and tell me what you need. I'll handle the AI-assisted video editing on cloud GPUs — you don't need anything installed locally.

Here's a typical use: you send a a 2-minute raw screen recording or phone video, ask for cut the silent pauses, add transitions, and export a clean final cut, 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 — shorter clips under 60 seconds process significantly faster and use fewer credits.

Matching Input to Actions

User prompts referencing video editing with openclaw, 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 calls go to https://mega-api-prod.nemovideo.ai. The main endpoints:

  1. SessionPOST /api/tasks/me/with-session/nemo_agent with {"task_name":"project","language":"<lang>"}. Gives you a session_id.
  2. Chat (SSE)POST /run_sse with session_id and your message in new_message.parts[0].text. Set Accept: text/event-stream. Up to 15 min.
  3. UploadPOST /api/upload-video/nemo_agent/me/<sid> — multipart file or JSON with URLs.
  4. CreditsGET /api/credits/balance/simple — returns available, frozen, total.
  5. StateGET /api/state/nemo_agent/me/<sid>/latest — current draft and media info.
  6. ExportPOST /api/render/proxy/lambda with render ID and draft JSON. Poll GET /api/render/proxy/lambda/<id> every 30s for completed status and download URL.

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

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

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

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.

Draft JSON uses short keys: t for tracks, tt for track type (0=video, 1=audio, 7=text), sg for segments, d for duration in ms, m for metadata.

Example timeline summary:

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

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

SSE Event Handling

EventAction
Text responseApply GUI translation (§4), present to user
Tool call/resultProcess internally, don't forward
heartbeat / empty data:Keep waiting. Every 2 min: "⏳ Still working..."
Stream closesProcess final response

~30% of editing operations return no text in the SSE stream. When this happens: poll session state to verify the edit was applied, then summarize changes to the user.

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 → "cut the silent pauses, add transitions, and export a clean final cut" → 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 "cut the silent pauses, add transitions, and export a clean final cut" — concrete instructions get better results.

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

Export as MP4 with H.264 codec for the widest compatibility across platforms.

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