Image To Video Converter Free

Turn five product photos in JPG format into 1080p animated video files just by typing what you need. Whether it's converting photo collections into shareable...

Security Scan

The skill's runtime instructions mostly match an image→video cloud API workflow, but there are inconsistencies about required config paths and a small scope creep (reading install path for headers); review the external domain, the NEMO_TOKEN use, and the config-path mismatch before installing.

Purpose & Capability

The skill claims to convert images to MP4 via a cloud render API and only requests a single credential (NEMO_TOKEN), which matches the stated purpose. However the SKILL.md frontmatter also references a config path (~/.config/nemovideo/) while the registry metadata listed no required config paths — that mismatch is unexplained and should be clarified.

Instruction Scope

Instructions focus on authenticating, creating a session, uploading files, streaming SSE, polling renders, and returning download URLs — all consistent with an image→video service. The instructions do direct the agent to derive an X-Skill-Platform header by inspecting install paths (e.g., ~/.clawhub/ or ~/.cursor/skills/), which implies reading the agent's filesystem to detect install location; this is peripheral to core functionality and worth questioning.

Install Mechanism

This is instruction-only with no install spec and no code files, so nothing is written to disk by an installer. That is the lowest-risk install model.

Credentials

Only one credential (NEMO_TOKEN) is declared as required, which is proportional for a cloud API. The SKILL.md also documents generating an anonymous token via the API if NEMO_TOKEN is missing — reasonable. The unexplained frontmatter mention of a config path (~/.config/nemovideo/) is inconsistent with the registry and could imply additional local config access.

Persistence & Privilege

always is false and the skill does not ask to persistently modify other skills or global agent settings. It stores session_id/token locally for the session, which is expected behavior for a networked service.

What to consider before installing

This skill appears to implement an expected cloud image→video workflow, but two things to verify before installing: (1) Confirm the external API domain (mega-api-prod.nemovideo.ai) is trustworthy and that you’re comfortable uploading images there — uploads will be transmitted to that server. (2) Clarify the config-path inconsistency: SKILL.md references ~/.config/nemovideo/ and reading install paths for an X-Skill-Platform header, but the registry metadata does not declare any config paths — ask the author why the skill needs to inspect filesystem paths and whether it will read anything beyond install location. If you don’t want a persistent token stored in your environment, prefer generating an anonymous token per-session (the skill documents how). Finally, avoid supplying highly sensitive images or credentials; limit the NEMO_TOKEN scope and rotate it if you later uninstall the skill.

Getting Started

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

Try saying:

• "convert five product photos in JPG format into a 1080p MP4"
• "turn these photos into a slideshow video with transitions and music"
• "converting photo collections into shareable videos for social media creators"

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.

Image to Video Converter Free — Convert Images into MP4 Videos

Drop your 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 five product photos in JPG format, ask for turn these photos into a slideshow video with transitions and music, 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 — using fewer than 20 images keeps processing fast and the video tight.

Matching Input to Actions

User prompts referencing image to video converter free, 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.

Headers are derived from this file's YAML frontmatter. X-Skill-Source is image-to-video-converter-free, 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).

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

Event	Action
Text response	Apply GUI translation (§4), present to user
Tool call/result	Process internally, don't forward
heartbeat / empty data:	Keep waiting. Every 2 min: "⏳ Still working..."
Stream closes	Process 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 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)

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

Common Workflows

Quick edit: Upload → "turn these photos into a slideshow video with transitions and music" → 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 these photos into a slideshow video with transitions and music" — concrete instructions get better results.

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

Export as MP4 for widest compatibility across platforms and devices.