Auto Generator

v1.0.0

Turn a 2-minute raw screen recording into 1080p auto-generated videos just by typing what you need. Whether it's automatically generating edited videos from...

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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 whitejohnk-26/auto-generator.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Auto Generator" (whitejohnk-26/auto-generator) from ClawHub.
Skill page: https://clawhub.ai/whitejohnk-26/auto-generator
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 auto-generator

ClawHub CLI

Package manager switcher

npx clawhub@latest install auto-generator
Security Scan
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Benign
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OpenClawOpenClaw
Benign
medium confidence
Purpose & Capability
Name/description (auto-generating edited videos) aligns with the runtime instructions (uploading footage, creating sessions, rendering/export endpoints). The single required env var NEMO_TOKEN is appropriate for an external API.
Instruction Scope
SKILL.md instructs the agent to call multiple nemovideo.ai endpoints (auth, session creation, SSE, upload, render) and to read the skill's YAML frontmatter and detect install path to set an X-Skill-Platform header. Those actions are coherent for a remote render service but do involve reading local paths and this SKILL.md file at runtime — consider whether you want the agent to probe filesystem install locations.
Install Mechanism
Instruction-only skill with no install spec or downloads. Low risk from installation mechanics because nothing is written or fetched as part of an installer.
Credentials
The skill requires a single API token (NEMO_TOKEN), which is proportionate. The SKILL.md frontmatter also references a config path (~/.config/nemovideo/) that the registry metadata did not list — this metadata mismatch should be clarified. The skill also implements an anonymous-token flow, so it can acquire a token itself if NEMO_TOKEN is absent.
Persistence & Privilege
always:false and no instructions to modify other skills or system-wide settings. The skill keeps session IDs for its own API interactions but does not request permanent agent-level privileges.
Assessment
This skill appears to do what it says: it uploads your footage to a remote service (mega-api-prod.nemovideo.ai) and uses a session token (NEMO_TOKEN) to create/render videos. Before installing: 1) Understand that any video you send will be processed by an external server — do not upload sensitive or private footage unless you trust the service and its privacy policy. 2) The skill can auto-acquire an anonymous token if you don't provide NEMO_TOKEN; that means the agent will contact the external auth endpoint automatically. 3) There is a small metadata inconsistency: the frontmatter mentions a config path (~/.config/nemovideo/) but the registry entry did not list config paths — ask the publisher to clarify why the skill might read local config directories. 4) The skill will attempt to read its frontmatter and detect install paths to set attribution headers — if you prefer the agent not probe filesystem locations, decline or audit runtime behavior. 5) Because the source/homepage is unknown, prefer to test with non-sensitive sample footage and verify outputs and network behavior before using with real content.

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

Runtime requirements

Clawdis
EnvNEMO_TOKEN
Primary envNEMO_TOKEN
latestvk973pf6cdmn42qa3d4zm520g9985j67k
36downloads
0stars
1versions
Updated 1d ago
v1.0.0
MIT-0

Getting Started

Send me your raw footage and I'll handle the AI video generation. Or just describe what you're after.

Try saying:

  • "generate a 2-minute raw screen recording into a 1080p MP4"
  • "automatically generate a polished video with cuts, transitions, and music"
  • "automatically generating edited videos from raw footage for 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.

Auto Generator — Generate Videos From Raw Footage

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

A quick example: upload a 2-minute raw screen recording, type "automatically generate a polished video with cuts, transitions, and music", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: shorter source clips produce faster and more accurate auto-generated results.

Matching Input to Actions

User prompts referencing auto generator, 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.

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

  • X-Skill-Source: auto-generator
  • X-Skill-Version: from frontmatter version
  • X-Skill-Platform: detect from install path (~/.clawhub/clawhub, ~/.cursor/skills/cursor, else 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 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

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.

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)

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "automatically generate a polished video with cuts, transitions, and music" — 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.

Common Workflows

Quick edit: Upload → "automatically generate a polished video with cuts, transitions, and 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.

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