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Free To Generator

v1.0.0

generate text or images into generated MP4 videos with this skill. Works with MP4, MOV, JPG, PNG files up to 200MB. content creators, marketers, students use...

0· 45·0 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 mory128/free-to-generator.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Free To Generator" (mory128/free-to-generator) from ClawHub.
Skill page: https://clawhub.ai/mory128/free-to-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 free-to-generator

ClawHub CLI

Package manager switcher

npx clawhub@latest install free-to-generator
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Purpose & Capability
The name/description match the runtime instructions: the SKILL.md details an API-based workflow for uploading media, creating sessions, streaming SSE, and exporting MP4s — which is coherent for a video-generation skill. Requiring a NEMO_TOKEN as the primary credential is proportional. However, SKILL.md's embedded metadata declares a config path (~/.config/nemovideo/) and logic that inspects the agent's install path to set an X-Skill-Platform header; those filesystem accesses are not reflected in the top-level registry fields (which list no config paths). That mismatch is unexpected and worth clarifying with the author.
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Instruction Scope
Most instructions stay within scope (create session, upload files, poll render status, read SSE). Concerns: (1) SKILL.md instructs the agent to detect install location (e.g. ~/.clawhub/, ~/.cursor/skills/) to set X-Skill-Platform, which implies reading filesystem paths; (2) the YAML frontmatter is used to derive headers and the metadata lists a config directory (~/.config/nemovideo/) — both are filesystem/config reads that aren't declared uniformly in the registry. The skill also instructs generating/storing session_id and tokens — acceptable for operation but potentially persistent. All external network calls go to mega-api-prod.nemovideo.ai, which is consistent with the purpose, but you should expect uploaded media and session metadata to be sent off-site.
Install Mechanism
No install spec and no code files: this is instruction-only. That minimizes disk-write and arbitrary code execution risk. The skill relies on making network calls to the vendor API rather than installing third-party binaries.
Credentials
Only one credential is declared (NEMO_TOKEN) and that aligns with the API-based design. The skill also provides a path to obtain an anonymous token via the vendor endpoint (UUID -> anonymous-token), which reduces the need to supply a long-lived secret. Still, the presence of configPaths in SKILL.md metadata suggests the skill may read or write files under ~/.config/nemovideo/ (not declared elsewhere). Requesting a token is justified, but confirm what the token grants and whether it will be stored on disk.
Persistence & Privilege
The skill is not always:on and does not request elevated platform privileges. It instructs saving session_id and using tokens for subsequent calls; it's not explicit where those are stored (memory vs disk). The implicit config path in the skill metadata suggests possible on-disk persistence of session/tokens, which should be confirmed. Autonomous invocation is allowed (default) but not in itself unusual.
What to consider before installing
This skill appears to do what it says (calls an external API to generate videos), but there are two things to check before enabling it: 1) confirm the mismatch about config access — SKILL.md references ~/.config/nemovideo/ and reading install paths (~/.clawhub/ etc.) while the registry metadata does not declare those config paths; ask the author whether the skill will read or write any files on your machine and where session tokens are stored. 2) Be aware that any files you upload (images, video, audio) and session metadata will be sent to mega-api-prod.nemovideo.ai; avoid uploading sensitive personal data or private media you don't want sent off-site. Prefer using the anonymous token flow if you don't want to supply a long-lived NEMO_TOKEN, and ask for the project's source or homepage for better trust before installing.

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

Runtime requirements

🎬 Clawdis
EnvNEMO_TOKEN
Primary envNEMO_TOKEN
latestvk974s8kpeda80ws8ss9kh8r2m185jxfp
45downloads
0stars
1versions
Updated 2d ago
v1.0.0
MIT-0

Getting Started

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

Try saying:

  • "generate a short text prompt or three product images into a 1080p MP4"
  • "generate a 30-second video from this product description"
  • "generating videos from text or images at no cost for content creators, marketers, students"

Automatic Setup

On first interaction, connect to the processing API before doing anything else. Show a brief status like "Setting things up...".

Token: If NEMO_TOKEN environment variable is already set, use it and skip to Session below.

Free token: Generate a UUID as client identifier, then POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id: <uuid>. The response field data.token becomes your NEMO_TOKEN (100 credits, 7-day expiry).

Session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Save session_id from the response.

Confirm to the user you're connected and ready. Don't print tokens or raw JSON.

Free Video Generator — Generate Videos From Text Free

Drop your text or images in the chat and tell me what you need. I'll handle the AI video generation on cloud GPUs — you don't need anything installed locally.

Here's a typical use: you send a a short text prompt or three product images, ask for generate a 30-second video from this product description, 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 — shorter prompts with clear descriptions produce more accurate results faster.

Matching Input to Actions

User prompts referencing free to 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.

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

Headers are derived from this file's YAML frontmatter. X-Skill-Source is free-to-generator, 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 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

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

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 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)

Common Workflows

Quick edit: Upload → "generate a 30-second video from this product description" → 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 "generate a 30-second video from this product description" — concrete instructions get better results.

Max file size is 200MB. Stick to MP4, MOV, JPG, PNG for the smoothest experience.

Export as MP4 for widest compatibility across platforms and devices.

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