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Adobe Video Editing

v1.0.0

edit raw video footage into polished edited clips with this skill. Works with MP4, MOV, AVI, MKV files up to 500MB. content creators and marketers use it for...

0· 111·0 current·0 all-time

Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for vynbosserman65/adobe-video-editing.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Adobe Video Editing" (vynbosserman65/adobe-video-editing) from ClawHub.
Skill page: https://clawhub.ai/vynbosserman65/adobe-video-editing
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

Canonical install target

openclaw skills install vynbosserman65/adobe-video-editing

ClawHub CLI

Package manager switcher

npx clawhub@latest install adobe-video-editing
Security Scan
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OpenClawOpenClaw
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medium confidence
!
Purpose & Capability
The skill claims the name 'Adobe Video Editing' but its runtime targets nemovideo.ai and uses a NEMO_TOKEN—there is no evidence it is an Adobe product or officially affiliated. The requested credential (NEMO_TOKEN) and API endpoints do align with the described cloud-rendering capability, but the use of the Adobe name is misleading.
Instruction Scope
SKILL.md stays within the editing/exporting domain (session creation, SSE, upload, export, credit checks). However it instructs the agent to automatically connect on first open and to silently obtain an anonymous token if none is present, and it instructs hiding raw token/API responses from the user—behaviors that can be surprising and reduce transparency about network activity.
Install Mechanism
Instruction-only skill with no install spec or code files; nothing is written to disk by an installer. This is lower risk from an installation perspective.
!
Credentials
Only one credential (NEMO_TOKEN) is required which is proportionate for a remote API, but the SKILL.md frontmatter references a config path (~/.config/nemovideo/) while the registry metadata lists no required config paths—this inconsistency in declared config access is concerning. Also the skill will generate and use anonymous tokens automatically if none are set.
Persistence & Privilege
always:false and no install hooks are good. The skill does instruct storing session_id for subsequent requests and the frontmatter references a config directory (possible persistent storage), but it doesn't specify where or how secrets/session IDs are stored. No elevated platform privileges are requested.
What to consider before installing
This skill appears to be a cloud-based video editor that talks to nemovideo.ai, but its public metadata and naming are inconsistent (it uses 'Adobe' in the name while calling a different provider). Before installing: 1) Be cautious with sensitive videos — files are uploaded to a third-party service. 2) The skill will automatically create an anonymous NEMO_TOKEN if you don't supply one and will connect to the remote backend on first use; if you prefer control, set your own NEMO_TOKEN rather than allowing automatic generation. 3) Ask the publisher for provenance and a homepage/privacy policy—there's no official site listed. 4) Clarify where session tokens are stored (in-memory vs written to ~/.config) and whether uploads or metadata are logged. 5) If you need stronger assurance, only install skills that clearly document the provider, data retention, and opt-in behavior. Additional information that would raise confidence: an official publisher/homepage, documentation showing affiliation with Adobe (if the name is legitimate), or explicit statements about how and where session tokens and uploads are stored.

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

Runtime requirements

🎬 Clawdis
EnvNEMO_TOKEN
Primary envNEMO_TOKEN
latestvk972w3mtmwe9v0areck37tpewx85410h
111downloads
0stars
1versions
Updated 1w ago
v1.0.0
MIT-0

Getting Started

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

Try saying:

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

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.

  1. Obtain a free token: Generate a random UUID as client identifier. POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id set to that UUID. The response data.token is your NEMO_TOKEN — 100 free credits, valid 7 days.
  2. Create a session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Authorization: Bearer <token>, Content-Type: application/json, and body {"task_name":"project","language":"<detected>"}. Store the returned session_id for all subsequent requests.

Keep setup communication brief. Don't display raw API responses or token values to the user.

Adobe Video Editing — Edit and Export Finished Videos

Send me your raw video footage and describe the result you want. The AI video editing runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload a 2-minute unedited screen recording, type "trim the pauses, add transitions, and export a clean final cut", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: shorter clips under 3 minutes process significantly faster and give more precise results.

Matching Input to Actions

User prompts referencing adobe video editing, 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-Sourceadobe-video-editing
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 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

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "trim the pauses, add transitions, and export a clean final cut" — concrete instructions get better results.

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

Export as MP4 with H.264 codec for the best balance of quality and file size.

Common Workflows

Quick edit: Upload → "trim the 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.

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