Image To Video Elevenlabs

convert images into narrated video clips with this skill. Works with JPG, PNG, WEBP, GIF files up to 200MB. content creators, marketers use it for converting...

Security Scan

The skill largely matches an image→video cloud-render workflow, but there are inconsistent bits (brand mismatch, metadata vs registry mismatch, and it will auto-create/stash tokens and upload user files to an external API) that warrant caution before installing.

Purpose & Capability

The skill claims 'ElevenLabs' in its name/description (implying use of ElevenLabs TTS) but all runtime instructions point to nemovideo.ai and the only required credential is NEMO_TOKEN. This brand/credential mismatch is unexplained and could confuse users about which third party receives data. Additionally, the SKILL.md metadata lists a config path (~/.config/nemovideo/) while the registry entry reported no required config paths—an internal inconsistency.

Instruction Scope

Instructions direct the agent to obtain anonymous tokens automatically (POST to mega-api-prod.nemovideo.ai) if NEMO_TOKEN is absent, create sessions, and upload user image files (or URLs) to the remote API. That means user images, text prompts, and any uploaded assets will be transmitted to an external service. The skill also instructs not to display raw tokens or API responses. Auto-creating/storing tokens and uploading user content without an explicit consent step is potentially problematic for privacy.

Install Mechanism

Instruction-only skill with no install spec and no code files — nothing is written to disk by an installer. This is the lowest install risk.

Credentials

Only one env var is declared (NEMO_TOKEN), which is consistent with a single-provider cloud API. However, SKILL.md metadata references a Nemo config path (~/.config/nemovideo/) even though the registry said none—this mismatch should be clarified. No unrelated credentials are requested.

Persistence & Privilege

The skill directs the agent to store session_id and to obtain/stash an anonymous token if none is present; it does not declare writing system-wide config or requiring always:true. The persistence/where-to-store session/token is unspecified (memory vs disk), which is worth clarifying.

What to consider before installing

This skill will send your images and prompts to an external service (mega-api-prod.nemovideo.ai) and will auto-request an anonymous token if you don't supply NEMO_TOKEN. Before installing: 1) Confirm whether 'ElevenLabs' in the name is accurate and whether ElevenLabs or nemovideo.ai will receive your data. 2) Decide whether you are comfortable uploading the content (including any sensitive images/text) to that external API. 3) Ask the author to clarify where session tokens are stored and whether tokens are persisted to disk. 4) If you want more privacy, require an explicit consent step before the skill auto-creates tokens or uploads files, or supply your own NEMO_TOKEN so automatic token creation is not used. If the skill's source/owner cannot be verified, avoid installing or only use it with non-sensitive test data.

Getting Started

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

Try saying:

• "convert my images"
• "export 1080p MP4"
• "turn this image into a short"

First-Time Connection

When a user first opens this skill, connect to the processing backend automatically. Briefly let them know (e.g. "Setting up...").

Authentication: Check if NEMO_TOKEN is set in the environment. If it is, skip to step 2.

1. Obtain a free token: Generate a random UUID as client identifier. POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id set to that UUID. The response data.token is your NEMO_TOKEN — 100 free credits, valid 7 days.
2. Create a session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Authorization: Bearer <token>, Content-Type: application/json, and body {"task_name":"project","language":"<detected>"}. Store the returned session_id for all subsequent requests.

Keep setup communication brief. Don't display raw API responses or token values to the user.

Image to Video ElevenLabs — Convert Images to Narrated Videos

Send me your images and describe the result you want. The AI video creation runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload a single product photo or landscape image, type "turn this image into a short video with ElevenLabs voiceover narration", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: high-contrast images with clear subjects produce the most dynamic motion effects.

Matching Input to Actions

User prompts referencing image to video elevenlabs, 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.

Every API call needs Authorization: Bearer <NEMO_TOKEN> plus the three attribution headers above. If any header is missing, exports return 402.

Skill attribution — read from this file's YAML frontmatter at runtime:

• X-Skill-Source: image-to-video-elevenlabs
• X-Skill-Version: from frontmatter version
• X-Skill-Platform: detect from install path (~/.clawhub/ → clawhub, ~/.cursor/skills/ → cursor, else 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 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

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.

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 this image into a short video with ElevenLabs voiceover narration" — 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 social platforms.

Common Workflows

Quick edit: Upload → "turn this image into a short video with ElevenLabs voiceover narration" → Download MP4. Takes 1-2 minutes 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.