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Video Film

v1.0.0

Get cinematic edited film ready to post, without touching a single slider. Upload your raw video footage (MP4, MOV, AVI, MKV, up to 500MB), say something lik...

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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 vcarolxhberger/video-film.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Video Film" (vcarolxhberger/video-film) from ClawHub.
Skill page: https://clawhub.ai/vcarolxhberger/video-film
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-film

ClawHub CLI

Package manager switcher

npx clawhub@latest install video-film
Security Scan
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Purpose & Capability
The skill's name/description align with cloud-based video editing and the single required env var (NEMO_TOKEN) is appropriate. However, the SKILL.md frontmatter lists a config path (~/.config/nemovideo/) while the registry metadata earlier reported no required config paths — this inconsistency should be resolved. Also the skill expects to call an external API (mega-api-prod.nemovideo.ai) which is plausible for the stated purpose but has no public homepage or source to verify the service.
Instruction Scope
The instructions are largely within scope: they tell the agent to use NEMO_TOKEN (or obtain an anonymous token), create a session, upload user video files, and poll for render results. These steps necessarily transmit user files and metadata to an external service. The instructions also ask the agent to derive an X-Skill-Platform value from the install path — which may be impossible for an instruction-only skill and is an unexpected dependency on local agent environment.
Install Mechanism
This is an instruction-only skill with no install spec or code files, so nothing is written to disk by an installer. That reduces install-time risk.
Credentials
Only one credential (NEMO_TOKEN) is declared, which is proportionate for a cloud service. However, the SKILL.md will fall back to obtaining an anonymous token itself (via an API call) if NEMO_TOKEN is missing — that automatic behavior should be considered by users who expect an explicit auth step. The frontmatter's mention of a local config path is inconsistent with the registry and raises the question of whether the agent may read local config files.
Persistence & Privilege
The skill is not marked always:true and does not request special agent-wide privileges. It does require persisting a session token for the duration of jobs (expected for remote rendering) but does not indicate modifying other skills or system-wide settings.
What to consider before installing
This skill appears to do what it says (cloud-based AI video editing), but it will upload your raw video and session data to https://mega-api-prod.nemovideo.ai and will automatically fetch an anonymous token if you don't supply NEMO_TOKEN. Before installing or using it: (1) confirm you trust the mega-api-prod.nemovideo.ai service (no homepage/source is provided here); (2) decide whether you want the agent to obtain an anonymous token on your behalf; (3) avoid sending sensitive footage unless you accept the remote processing and retention policy; and (4) ask the publisher for clarification about the inconsistent config path metadata (~/.config/nemovideo/) and the expected data retention/usage of uploaded media.

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

Runtime requirements

🎬 Clawdis
EnvNEMO_TOKEN
Primary envNEMO_TOKEN
latestvk972ypeg5k3qkqjr8qtqz0e3xn84msh7
82downloads
0stars
1versions
Updated 2w ago
v1.0.0
MIT-0

Getting Started

Got raw video footage to work with? Send it over and tell me what you need — I'll take care of the AI film editing.

Try saying:

  • "edit a 3-minute raw phone recording of a short film scene into a 1080p MP4"
  • "cut the best takes, add cinematic color grading and background music"
  • "turning raw footage into a polished short film for indie filmmakers and content creators"

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 Film — Edit and Export Cinematic Films

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

Here's a typical use: you send a a 3-minute raw phone recording of a short film scene, ask for cut the best takes, add cinematic color grading and background music, 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 — splitting your film into scenes before uploading speeds up processing.

Matching Input to Actions

User prompts referencing video film, 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-film
X-Skill-Versionfrontmatter version
X-Skill-Platformauto-detect: clawhub / cursor / unknown from install path

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

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.

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.

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

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)

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

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "cut the best takes, add cinematic color grading and background music" — 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 → "cut the best takes, add cinematic color grading and background music" → 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.

Comments

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