Gif Converter

v1.0.0

convert GIF files into converted MP4 files with this skill. Works with GIF, WEBP, APNG, MP4 files up to 200MB. social media creators use it for converting GI...

0· 78·0 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/gif-converter.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Gif Converter" (peand-rover/gif-converter) from ClawHub.
Skill page: https://clawhub.ai/peand-rover/gif-converter
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 gif-converter

ClawHub CLI

Package manager switcher

npx clawhub@latest install gif-converter
Security Scan
VirusTotalVirusTotal
Benign
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OpenClawOpenClaw
Benign
medium confidence
Purpose & Capability
The name/description (GIF → MP4 conversion) align with the runtime instructions: the SKILL.md describes creating a session, uploading files, rendering, and returning a download URL on a nemo video backend. Requesting a NEMO_TOKEN credential is reasonable for this integration.
Instruction Scope
Instructions stay largely within the conversion task (auth, session creation, upload, render/poll, download). They require sending user files to https://mega-api-prod.nemovideo.ai and include SSE/video-edit workflows. Minor scope issues: the skill tells the agent to 'detect the install path' to set X-Skill-Platform (which would require checking host paths) and expects attribution headers derived from the skill file — these are implementation details but may cause the agent to inspect filesystem paths or the skill file.
Install Mechanism
No install spec or external downloads are provided (instruction-only), so nothing is written to disk by an installer. This is lower risk.
Credentials
The skill declares a single primary env var (NEMO_TOKEN), which fits the stated backend API usage. However metadata also lists a config path (~/.config/nemovideo/) that is not referenced in the SKILL.md instructions — this mismatch is unexplained and could indicate the skill expects to read a local config/token although the runtime instructions prefer an environment variable or anonymous-token flow.
Persistence & Privilege
always:false and default autonomous invocation are normal. The skill does not request global/system modifications and does not declare writing other skills' configs. The only extra privilege implied is potential read access to the user's home config path (per metadata), which you should confirm with the platform before granting.
Assessment
This skill uploads files you give it to an external service (mega-api-prod.nemovideo.ai). It will use a NEMO_TOKEN from the environment if present or obtain an anonymous token automatically. Before installing: 1) confirm you trust nemo‑video (privacy of uploaded media); 2) avoid supplying sensitive content unless you control the destination; 3) prefer using an account token you control rather than relying on anonymous tokens; 4) ask the platform whether the skill will be allowed to read ~/.config/nemovideo/ or inspect install paths (the skill's metadata lists that path but the instructions don't clearly use it); and 5) note the skill's source/homepage are unknown — lack of provenance increases risk. If you need higher assurance, request the skill's source or an official integration from the service owner.

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

Runtime requirements

🎞️ Clawdis
EnvNEMO_TOKEN
Primary envNEMO_TOKEN
latestvk97bd8zew6vc9z8gm5vdy50fn585dzyk
78downloads
0stars
1versions
Updated 5d ago
v1.0.0
MIT-0

Getting Started

Send me your GIF files and I'll handle the GIF to video conversion. Or just describe what you're after.

Try saying:

  • "convert a 3-second looping GIF animation into a 1080p MP4"
  • "convert this GIF to an MP4 video file"
  • "converting GIF animations into shareable MP4 videos for social media creators"

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.

GIF Converter — Convert GIFs to MP4 Videos

This tool takes your GIF files and runs GIF to video conversion through a cloud rendering pipeline. You upload, describe what you want, and download the result.

Say you have a 3-second looping GIF animation and want to convert this GIF to an MP4 video file — the backend processes it in about under 30 seconds and hands you a 1080p MP4.

Tip: shorter GIFs with fewer frames convert faster and produce smaller file sizes.

Matching Input to Actions

User prompts referencing gif converter, 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 gif-converter, 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

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)

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "convert this GIF to an MP4 video file" — concrete instructions get better results.

Max file size is 200MB. Stick to GIF, WEBP, APNG, MP4 for the smoothest experience.

Export as MP4 for widest compatibility across all social platforms and devices.

Common Workflows

Quick edit: Upload → "convert this GIF to an MP4 video file" → Download MP4. Takes under 30 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.

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