Ai Image To Video Gratis

Skip the learning curve of professional editing software. Describe what you want — turn my photos into a smooth video with transitions — and get animated vid...

Security Scan

The skill's requests and instructions are generally consistent with a cloud image-to-video service (it needs a NEMO_TOKEN and talks to nemovideo APIs), but there are small metadata inconsistencies and normal privacy/exfiltration considerations you should understand before uploading files or allowing the agent to acquire/store tokens.

Purpose & Capability

Name/description match the runtime instructions: calls a nemo video backend, uploads image files, creates sessions, renders and returns download URLs. Requiring NEMO_TOKEN is coherent for a hosted API. Note: the SKILL.md frontmatter lists a config path (~/.config/nemovideo/) while the registry metadata above said no config paths — this is a minor inconsistency.

Instruction Scope

Instructions stay within the stated purpose: check for NEMO_TOKEN, obtain an anonymous token if missing, create a session, upload images, stream SSE, and poll a render endpoint. The skill expects to accept local file paths or URLs and will upload those files to the third-party API — which is expected for this use-case but means any file you point it at will be transmitted to the service. The instructions do not ask the agent to read arbitrary unrelated system files or unrelated environment variables.

Install Mechanism

No install spec and no code files — instruction-only. This minimizes installation risk because nothing is written to disk by an installer in advance.

Credentials

Only one declared credential (NEMO_TOKEN / primaryEnv) is required, which matches the API usage. The skill also describes a flow to obtain an anonymous token if NEMO_TOKEN is absent. Consider whether you want an agent to auto-acquire and retain that token on your behalf. There are no other unrelated secrets requested.

Persistence & Privilege

always:false and no instructions to modify other skills or global agent settings. The skill keeps a session_id for job operations (expected). The only slight concern is the SKILL.md frontmatter listing a config path (~/.config/nemovideo/) — if the agent actually reads or writes that path it would create local persistence; the registry metadata earlier contradicts this, so confirm intended behavior.

Assessment

This skill appears to do what it says: it will upload images you give it to a third‑party cloud service (mega-api-prod.nemovideo.ai) and return rendered videos. Before installing or using it: 1) Do not upload sensitive images or files you don't want sent to an external service. 2) Confirm whether you want the agent to auto-acquire and store an anonymous NEMO_TOKEN; prefer using a token you control if you care about provenance/retention. 3) Ask the publisher (or inspect runtime) to clarify the config path behavior (~/.config/nemovideo/) because the registry metadata and SKILL.md disagree. 4) If you need stronger assurance, verify the service domain and privacy/retention policy for nemovideo, and restrict the agent's file-access scope so it can only read images you explicitly provide.

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 my photos into a smooth"

Quick Start Setup

This skill connects to a cloud processing backend. On first use, set up the connection automatically and let the user know ("Connecting...").

Token check: Look for NEMO_TOKEN in the environment. If found, skip to session creation. Otherwise:

• Generate a UUID as client identifier
• POST https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with X-Client-Id header
• Extract data.token from the response — this is your NEMO_TOKEN (100 free credits, 7-day expiry)

Session: POST https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Keep the returned session_id for all operations.

Let the user know with a brief "Ready!" when setup is complete. Don't expose tokens or raw API output.

AI Image to Video Gratis — Convert Images to Video Free

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 three product photos in JPG format, ask for turn my photos into a smooth video with transitions, 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 images with high contrast speeds up processing noticeably.

Matching Input to Actions

User prompts referencing ai image to video gratis, 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.

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.

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

Header	Value
X-Skill-Source	ai-image-to-video-gratis
X-Skill-Version	frontmatter version
X-Skill-Platform	auto-detect: clawhub / cursor / unknown from install path

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)

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "turn my photos into a smooth video with transitions" — 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.

Common Workflows

Quick edit: Upload → "turn my photos into a smooth video with transitions" → 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.