Free Video Generation From Image

v1.0.0

Turn a single product photo or landscape image into 1080p animated video clips just by typing what you need. Whether it's converting static images into short...

0· 46·0 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 vynbosserman65/free-video-generation-from-image.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Free Video Generation From Image" (vynbosserman65/free-video-generation-from-image) from ClawHub.
Skill page: https://clawhub.ai/vynbosserman65/free-video-generation-from-image
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-generation-from-image

ClawHub CLI

Package manager switcher

npx clawhub@latest install free-video-generation-from-image
Security Scan
VirusTotalVirusTotal
Benign
View report →
OpenClawOpenClaw
Benign
medium confidence
Purpose & Capability
The skill is a cloud-backed image→video service and declares NEMO_TOKEN as its primary credential, which is coherent: the instructions call the remote nemo API for uploads, SSE streams, rendering, and downloads. One minor inconsistency: the SKILL.md frontmatter lists a config path (~/.config/nemovideo/) in metadata, while the registry summary shows no required config paths; this could indicate the skill may look for a local config file but the registry metadata wasn't updated.
Instruction Scope
The SKILL.md explicitly instructs the agent to upload user image files to an external API, create sessions, stream SSE responses, poll render status, and return download URLs — all within the advertised purpose. It also provides a fallback that generates an anonymous token by POSTing to the service if NEMO_TOKEN isn't present. The file tells the agent to 'keep the technical details out of the chat,' which is a design choice but reduces transparency about network activity. The instructions do not request unrelated system files or other environment variables.
Install Mechanism
This is instruction-only (no install spec, no code files). Nothing is written to disk by the skill itself during install — lowest-risk install mechanism.
Credentials
The only declared credential is NEMO_TOKEN (primaryEnv), which is proportional for an external API service. However, the SKILL.md frontmatter also references a local config path (~/.config/nemovideo/), which may imply the agent could try to read a local token/config if present — registry metadata did not list this as a required config path. This mismatch is worth confirming before installing. The fallback anonymous-token workflow means the skill can operate without user-supplied secrets.
Persistence & Privilege
The skill is not force-included (always: false) and does not request elevated or persistent agent privileges. It does not modify other skills or system-wide settings per the provided instructions.
Assessment
What to consider before installing: - This skill uploads images and related data to an external service (mega-api-prod.nemovideo.ai). Only install it if you trust that external provider and are comfortable with your images being sent to their servers. - The skill expects a NEMO_TOKEN. If you don't supply one it will obtain an anonymous token itself by contacting the provider — this is normal but means network calls occur automatically. - Confirm whether the skill will read a local config (~/.config/nemovideo/). The registry metadata said no config paths, but SKILL.md mentions one; ask the author to clarify if the agent will attempt to read local files. - Avoid supplying any sensitive or production credentials; the service needs only its own API token for operation. If you need stronger privacy guarantees, verify the provider's privacy policy and where data is stored/retained. - If you want higher assurance, request more info: the actual network endpoints and domain reputation, whether uploads are encrypted at rest, retention policy for uploaded images/videos, and whether the skill will log or transmit additional metadata beyond the uploaded files. Confidence rationale: The skill is functionally consistent with its purpose and asks for a single, proportional credential, so 'benign' is appropriate; confidence is 'medium' because the skill source is unknown, the remote API domain is unverified here, and there is a small mismatch about a local config path in SKILL.md metadata.

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

Runtime requirements

🖼️ Clawdis
EnvNEMO_TOKEN
Primary envNEMO_TOKEN
latestvk9777y2gsztj1nmwjxyk39hxvh85k9js
46downloads
0stars
1versions
Updated 2d ago
v1.0.0
MIT-0

Getting Started

Share your still images and I'll get started on AI video creation. Or just tell me what you're thinking.

Try saying:

  • "convert my still images"
  • "export 1080p MP4"
  • "turn this image into a 10-second"

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 Generation from Image — Convert Images into Video Clips

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

Here's a typical use: you send a a single product photo or landscape image, ask for turn this image into a 10-second animated video clip, and about 30-60 seconds later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.

One thing worth knowing — high-contrast images with clear subjects produce smoother motion results.

Matching Input to Actions

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

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

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.

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

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)

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

Common Workflows

Quick edit: Upload → "turn this image into a 10-second animated video clip" → 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.

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "turn this image into a 10-second animated video clip" — concrete instructions get better results.

Max file size is 50MB. Stick to JPG, PNG, WEBP, HEIC for the smoothest experience.

Export as MP4 for widest compatibility across all social platforms.

Comments

Loading comments...