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Free Video Easy

v1.0.0

Turn a 2-minute smartphone recording into 1080p polished MP4 clips just by typing what you need. Whether it's quickly editing raw footage into shareable vide...

0· 47·0 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 tk8544-b/free-video-easy.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Free Video Easy" (tk8544-b/free-video-easy) from ClawHub.
Skill page: https://clawhub.ai/tk8544-b/free-video-easy
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 free-video-easy

ClawHub CLI

Package manager switcher

npx clawhub@latest install free-video-easy
Security Scan
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medium confidence
Purpose & Capability
The declared purpose (cloud AI video editing) matches the runtime instructions (upload, session, SSE, render/export). However the registry metadata (required config paths: none) conflicts with the SKILL.md frontmatter which declares a config path (~/.config/nemovideo/). Also the registry marks NEMO_TOKEN as required while the SKILL.md describes a fallback anonymous-token flow — so the env requirement appears overstated.
Instruction Scope
Instructions stay within video-editing scope: create session, upload video, run SSE, poll render status, return download URL. They do instruct the agent to read this file's YAML frontmatter for attribution and to detect an install path (~/.clawhub/, ~/.cursor/skills/) — that requires the agent to inspect install location / skill file metadata, which is plausible but should be explicit. All user media is sent to a third-party API endpoint; that is expected but has privacy implications.
Install Mechanism
Instruction-only skill with no install spec or code files — lowest-risk delivery method. Nothing is downloaded or written to disk by an installer.
Credentials
Only a single credential (NEMO_TOKEN) is declared, which is proportionate to a cloud API. But SKILL.md documents an anonymous-token fallback if NEMO_TOKEN is not present, so marking NEMO_TOKEN as strictly required in the registry is inconsistent. The skill will upload user video to an external domain (mega-api-prod.nemovideo.ai) — providing a long-lived NEMO_TOKEN grants that service access to your uploads, so users should treat the token as sensitive.
Persistence & Privilege
The skill does not request always:true, does not modify other skills, and has no install hooks. Autonomous invocation is allowed (the platform default) but that alone is not a red flag here.
What to consider before installing
This skill appears to do what it claims (cloud AI video editing), but check the following before installing or giving it a token: 1) Verify the API domain (mega-api-prod.nemovideo.ai) and the service's privacy policy — uploading videos sends your media off-device. 2) Prefer using the anonymous-token flow (the SKILL.md supports it) instead of providing a long-lived NEMO_TOKEN, unless you trust the service. 3) Ask the publisher to resolve metadata inconsistencies: the registry says no configPaths and that NEMO_TOKEN is required, while SKILL.md lists a config path (~/.config/nemovideo/) and allows anonymous tokens. 4) Confirm what the NEMO_TOKEN scope is and whether it can be revoked. 5) If the videos contain sensitive content, do not upload them until you are satisfied with the service and token handling. If you want the reviewer to be more confident, provide the service's official homepage, source, or a link to a privacy/security policy so the backend domain and token model can be validated.

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

Runtime requirements

🎬 Clawdis
EnvNEMO_TOKEN
Primary envNEMO_TOKEN
latestvk97evjfnez8q2rwsq54kapeymn85j10j
47downloads
0stars
1versions
Updated 2d 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 clip, add background music,"

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.

Free Video Easy — Edit and Export Videos Free

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

Say you have a 2-minute smartphone recording and want to trim the clip, add background music, and export it ready to share — the backend processes it in about 30-60 seconds and hands you a 1080p MP4.

Tip: shorter clips under 60 seconds process significantly faster.

Matching Input to Actions

User prompts referencing free video easy, 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.

Skill attribution — read from this file's YAML frontmatter at runtime:

  • X-Skill-Source: free-video-easy
  • X-Skill-Version: from frontmatter version
  • X-Skill-Platform: detect from install path (~/.clawhub/clawhub, ~/.cursor/skills/cursor, else unknown)

Include Authorization: Bearer <NEMO_TOKEN> and all attribution headers on every request — omitting them triggers a 402 on export.

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)

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

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.

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 clip, add background music, and export it ready to share" — 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 and devices.

Common Workflows

Quick edit: Upload → "trim the clip, add background music, and export it ready to share" → Download MP4. Takes 30-60 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.

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