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Video Editor Ai Best

v1.0.0

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

0· 62·0 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 francemichaell-15/video-editor-ai-best.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Video Editor Ai Best" (francemichaell-15/video-editor-ai-best) from ClawHub.
Skill page: https://clawhub.ai/francemichaell-15/video-editor-ai-best
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-editor-ai-best

ClawHub CLI

Package manager switcher

npx clawhub@latest install video-editor-ai-best
Security Scan
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Suspicious
medium confidence
Purpose & Capability
The skill claims to perform cloud video editing and requires a single API token (NEMO_TOKEN), which is coherent. However the SKILL.md frontmatter declares a config path (~/.config/nemovideo/) while the registry metadata shows no required config paths, and the skill has no homepage or verifiable source — this mismatch and missing provenance reduce confidence.
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Instruction Scope
Runtime instructions tell the agent to read NEMO_TOKEN (or obtain an anonymous token), create sessions, upload files (multipart or by URL), and poll a third-party API at https://mega-api-prod.nemovideo.ai. The instructions also expect to auto-detect an install path for an attribution header. These steps legitimately support a cloud editor, but they also involve reading env vars, potentially a local config path, and uploading user files to an external, unverified domain — all of which expand the data-access surface and could be used to exfiltrate sensitive content if the backend is untrusted.
Install Mechanism
No install spec and no code files — this is instruction-only, so nothing is written to disk by an installer. That minimizes installation-time risk.
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Credentials
Only NEMO_TOKEN is declared as required, which is reasonable for an API-backed service. But the SKILL.md/frontmatter also references a config path (~/.config/nemovideo/), suggesting the skill may read local config files for credentials; that was not reflected in the registry metadata. The discrepancy and the potential to access a local config containing tokens is disproportionate without clearer justification.
Persistence & Privilege
The skill is not force-enabled (always: false) and does not request system-wide persistence. Autonomous invocation is allowed (the platform default), which is expected for a skill of this type. There is no install-time modification of other skills or system settings described.
What to consider before installing
This skill looks like a cloud-based video editor and asks for one API token (NEMO_TOKEN) and will upload your files to https://mega-api-prod.nemovideo.ai. Before installing: 1) Verify the service owner and domain (there's no homepage or repo linked). 2) Prefer using a short‑lived or limited-scope token rather than a long-lived credential. 3) Check for and remove any sensitive tokens in ~/.config/nemovideo/ (the SKILL.md references that path). 4) Test with a small, non-sensitive clip first. 5) If you are uncomfortable with automatic uploads to an external server, do not enable the skill or disable autonomous invocation. 6) If you need higher assurance, ask the publisher for provenance (homepage/repo, privacy policy) and clarification about why the config path was omitted from the registry metadata.

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

Runtime requirements

🎬 Clawdis
EnvNEMO_TOKEN
Primary envNEMO_TOKEN
latestvk97f861hfbbab5fnqm3mm5e0b184yzjd
62downloads
0stars
1versions
Updated 1w ago
v1.0.0
MIT-0

Getting Started

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

Try saying:

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

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.

Best AI Video Editor — Edit and Export Polished Videos

This tool takes your raw video footage and runs AI-powered video editing through a cloud rendering pipeline. You upload, describe what you want, and download the result.

Say you have a 3-minute unedited screen recording and want to cut the pauses, add transitions, and export a clean final video — the backend processes it in about 1-2 minutes and hands you a 1080p MP4.

Tip: shorter clips under 2 minutes process significantly faster.

Matching Input to Actions

User prompts referencing video editor ai best, 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.

Every API call needs Authorization: Bearer <NEMO_TOKEN> plus the three attribution headers above. If any header is missing, exports return 402.

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

HeaderValue
X-Skill-Sourcevideo-editor-ai-best
X-Skill-Versionfrontmatter version
X-Skill-Platformauto-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

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.

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)

Tips and Tricks

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

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

Export as MP4 for widest compatibility across platforms.

Common Workflows

Quick edit: Upload → "cut the pauses, add transitions, and export a clean final video" → 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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