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dsewell-583h0

Francais Photo Video Maker

by dsewell-583h0 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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Install in OpenClaw
/install francais-photo-video-maker
Description
Cloud-based francais-photo-video-maker tool that handles creating French-language videos from photos. Upload JPG, PNG, WEBP, HEIC files (up to 200MB), descri...
README (SKILL.md)

Getting Started

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

Try saying:

  • "turn my photos and images"
  • "export 1080p MP4"
  • "créer une vidéo en français avec"

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.

Français Photo Video Maker — Turn Photos Into French Videos

Drop your photos and 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 ten vacation photos in JPEG format, ask for créer une vidéo en français avec mes photos et ajouter de la musique, 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 — fewer photos with longer durations produce smoother-feeling videos.

Matching Input to Actions

User prompts referencing francais photo video maker, aspect ratio, text overlays, or audio tracks get routed to the corresponding action via keyword and intent classification.

User says... Action Skip 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.

Base URL: https://mega-api-prod.nemovideo.ai

Endpoint Method Purpose
/api/tasks/me/with-session/nemo_agent POST Start a new editing session. Body: {"task_name":"project","language":"\x3Clang>"}. Returns session_id.
/run_sse POST Send a user message. Body includes app_name, session_id, new_message. Stream response with Accept: text/event-stream. Timeout: 15 min.
/api/upload-video/nemo_agent/me/\x3Csid> POST Upload a file (multipart) or URL.
/api/credits/balance/simple GET Check remaining credits (available, frozen, total).
/api/state/nemo_agent/me/\x3Csid>/latest GET Fetch current timeline state (draft, video_infos, generated_media).
/api/render/proxy/lambda POST Start export. Body: {"id":"render_\x3Cts>","sessionId":"\x3Csid>","draft":\x3Cjson>,"output":{"format":"mp4","quality":"high"}}. Poll status every 30s.

Accepted file types: mp4, mov, avi, webm, mkv, jpg, png, gif, webp, mp3, wav, m4a, aac.

Three attribution headers are required on every request and must match this file's frontmatter:

Header Value
X-Skill-Source francais-photo-video-maker
X-Skill-Version frontmatter version
X-Skill-Platform auto-detect: clawhub / cursor / unknown from install path

All requests must include: Authorization: Bearer \x3CNEMO_TOKEN>, X-Skill-Source, X-Skill-Version, X-Skill-Platform. Missing attribution headers will cause export to fail with 402.

Error Handling

Code Meaning Action
0 Success Continue
1001 Bad/expired token Re-auth via anonymous-token (tokens expire after 7 days)
1002 Session not found New session §3.0
2001 No credits Anonymous: show registration URL with ?bind=\x3Cid> (get \x3Cid> from create-session or state response when needed). Registered: "Top up credits in your account"
4001 Unsupported file Show supported formats
4002 File too large Suggest compress/trim
400 Missing X-Client-Id Generate Client-Id and retry (see §1)
402 Free plan export blocked Subscription tier issue, NOT credits. "Register or upgrade your plan to unlock export."
429 Rate limit (1 token/client/7 days) Retry in 30s once

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.

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 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 → "créer une vidéo en français avec mes photos et ajouter de la musique" → 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 "créer une vidéo en français avec mes photos et ajouter de la musique" — concrete instructions get better results.

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

Export as MP4 for widest compatibility across French social platforms.

Usage Guidance
This skill appears to implement a cloud-based French photo→video workflow and will send any images you provide (and an auth token) to https://mega-api-prod.nemovideo.ai. Before installing or using it: 1) Be cautious about uploading sensitive photos (personal, legal, proprietary) because they will leave your machine. 2) Verify the service provenance — there is no homepage or source repo listed; ask the publisher for an official domain, privacy policy, or source code. 3) Note the manifest inconsistency: SKILL.md references ~/.config/nemovideo/ while registry metadata lists no config paths — ask the author why. 4) Treat NEMO_TOKEN like a password; don’t reuse other service credentials here. 5) If you need stronger assurance, request the skill’s source code or an official endpoint confirmation and check their data retention/privacy terms; otherwise consider using an alternative with verifiable provenance.
Capability Analysis
Type: OpenClaw Skill Name: francais-photo-video-maker Version: 1.0.0 The skill facilitates cloud-based video creation by interacting with the external API 'mega-api-prod.nemovideo.ai'. It requires risky capabilities including access to environment variables (NEMO_TOKEN), local configuration directories (~/.config/nemovideo/), and the ability to upload user files to a remote server. While these actions are aligned with the stated purpose of a cloud video maker, the instructions also require the agent to auto-detect its installation environment (e.g., 'clawhub' or 'cursor') for telemetry and generate anonymous tokens, which increases the attack surface. Files: SKILL.md, _meta.json.
Capability Assessment
Purpose & Capability
The name/description (cloud French photo→video maker) aligns with the network API endpoints and the single required credential (NEMO_TOKEN). However, the SKILL.md frontmatter declares a config path (~/.config/nemovideo/) while the registry metadata lists no required config paths — that mismatch is unexpected. Also there is no homepage or source repo listed, so the service provenance is unknown.
Instruction Scope
The instructions direct the agent to upload user-supplied files and manage a session token with the third-party API (mega-api-prod.nemovideo.ai). If NEMO_TOKEN is missing the agent will generate a UUID and obtain an anonymous token from the remote API — i.e., the skill will perform network calls and transmit uploaded files and derived tokens to an external service. The SKILL.md also asks the agent to 'auto-detect' platform from an install path (which could require reading filesystem/install-path info) and to 'keep technical details out of the chat' (which hides operational details from the user). These actions are coherent with the stated purpose but increase privacy/exfiltration risk for uploaded images and metadata.
Install Mechanism
There is no install spec and no code files — the skill is instruction-only. That minimizes on-disk installation risk.
Credentials
Only one credential is declared (NEMO_TOKEN) which is appropriate for a hosted API. The SKILL.md behaviour of falling back to an anonymously-provisioned 7-day token is plausible. Still, because uploads (images/audio) will be sent to an external API, users should treat NEMO_TOKEN as sensitive and avoid providing other unrelated credentials. The mismatch between frontmatter configPaths and registry 'no config paths' is noted.
Persistence & Privilege
The skill is not marked 'always' and does not request elevated or persistent platform privileges. It does require maintaining a session_id for in-flight jobs, which is normal for a cloud render workflow.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install francais-photo-video-maker
  3. After installation, invoke the skill by name or use /francais-photo-video-maker
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release of Français Photo Video Maker. - Create French-language videos from uploaded photos (JPG, PNG, WEBP, HEIC up to 200MB) - Supports fast 1080p MP4 video export in 30–60 seconds - Automatic handling of user tokens with up to 100 free credits for new users - Easy drag-and-drop photo upload and simple, natural-language prompts - Built-in workflows for adding music, text overlays, and more - Clear user feedback on connection, export status, and errors - Designed for French-speaking content creators working with images
Metadata
Slug francais-photo-video-maker
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Francais Photo Video Maker?

Cloud-based francais-photo-video-maker tool that handles creating French-language videos from photos. Upload JPG, PNG, WEBP, HEIC files (up to 200MB), descri... It is an AI Agent Skill for Claude Code / OpenClaw, with 76 downloads so far.

How do I install Francais Photo Video Maker?

Run "/install francais-photo-video-maker" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Francais Photo Video Maker free?

Yes, Francais Photo Video Maker is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Francais Photo Video Maker support?

Francais Photo Video Maker is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Francais Photo Video Maker?

It is built and maintained by dsewell-583h0 (@dsewell-583h0); the current version is v1.0.0.

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