Ai Video Drama

v1.0.0

create video clips into cinematic drama videos with this skill. Works with MP4, MOV, AVI, WebM files up to 500MB. filmmakers, content creators, social media...

0· 67·0 current·0 all-time
bypeandrover adam@peand-rover

Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for peand-rover/ai-video-drama.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Ai Video Drama" (peand-rover/ai-video-drama) from ClawHub.
Skill page: https://clawhub.ai/peand-rover/ai-video-drama
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 ai-video-drama

ClawHub CLI

Package manager switcher

npx clawhub@latest install ai-video-drama
Security Scan
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OpenClawOpenClaw
Benign
high confidence
Purpose & Capability
Name/description (cloud GPU rendering of video clips) matches the declared env var (NEMO_TOKEN) and the SKILL.md which instructs the agent to call a nemo video-rendering backend. Required credentials and API endpoints align with the stated purpose.
Instruction Scope
Most instructions stay within scope (establish session, upload files, request renders, poll for output). However, the SKILL.md indicates detection of an install path to set an attribution header and includes metadata configPaths (~/.config/nemovideo/). Determining X-Skill-Platform or consulting that config path could cause the agent to probe the user's filesystem (home directories) to derive platform or read stored Nemo config. This is minor for functionality but is a databreach/privacy surface the user should be aware of.
Install Mechanism
Instruction-only skill with no install spec or downloaded code. Nothing is written to disk by the skill itself during installation (lowest install risk).
Credentials
Only one credential is required (NEMO_TOKEN, with anonymous-token fallback). That is proportional to a service that authenticates API requests. The metadata's configPaths could let the agent look for local Nemo configuration, which is plausible but worth noting as a potential source of additional tokens/config if present.
Persistence & Privilege
Skill is not always-enabled and does not request system-wide modification. It will, however, make network calls and upload user-supplied media to the external nemo API when invoked. Autonomous invocation is allowed by default (platform normal), so be mindful that the agent can call the remote API and transmit files when the skill runs.
Assessment
This skill behaves like a typical cloud video-rendering integration: it will send files you provide to https://mega-api-prod.nemovideo.ai and uses a NEMO_TOKEN (or will get a short-lived anonymous token) to authenticate. Before installing or using it, consider: 1) Only upload video/audio you are comfortable sending to an external service; avoid embedding secrets or sensitive visuals in media. 2) Provide a dedicated or ephemeral NEMO_TOKEN rather than a broad-purpose credential, and review nemo's privacy/terms for retention and sharing. 3) The skill may inspect ~/.config/nemovideo/ and attempt to detect install paths to set attribution headers — this can reveal parts of your home directory structure or stored nemo config; if that concerns you, avoid populating those paths or decline to set a persistent token. 4) Tokens issued via the anonymous-token endpoint expire in 7 days and there are per-client limits; the skill describes how it will re-auth and handle error codes—read those sections if you care about billing/credits. Overall the skill is coherent with its stated purpose, but treat it like any third-party cloud service and verify you trust the mega-api-prod.nemovideo.ai domain before sending private content.

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

Runtime requirements

🎭 Clawdis
EnvNEMO_TOKEN
Primary envNEMO_TOKEN
latestvk97944krrrnb4xn720k5qk3ze1853c6c
67downloads
0stars
1versions
Updated 1w ago
v1.0.0
MIT-0

Getting Started

Share your video clips and I'll get started on AI drama enhancement. Or just tell me what you're thinking.

Try saying:

  • "create my video clips"
  • "export 1080p MP4"
  • "add dramatic music, color grading, 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.

AI Video Drama — Create Cinematic Drama Videos

Send me your video clips and describe the result you want. The AI drama enhancement runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload a 2-minute raw scene recording, type "add dramatic music, color grading, and cinematic cuts to my scene", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: shorter scenes under 3 minutes get more precise dramatic pacing.

Matching Input to Actions

User prompts referencing ai video drama, 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 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.

Headers are derived from this file's YAML frontmatter. X-Skill-Source is ai-video-drama, X-Skill-Version comes from the version field, and X-Skill-Platform is detected from the install path (~/.clawhub/ = clawhub, ~/.cursor/skills/ = cursor, otherwise unknown).

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 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

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.

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)

Common Workflows

Quick edit: Upload → "add dramatic music, color grading, and cinematic cuts to my scene" → 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 "add dramatic music, color grading, and cinematic cuts to my scene" — 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 streaming and social platforms.

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