Ai Image To Video Canva

Skip the learning curve of professional editing software. Describe what you want — turn my images into a short animated video with transitions and music — an...

Security Scan

The skill’s behavior (uploading images and calling a remote nemo-video API) matches its stated purpose, but there are provenance and metadata inconsistencies and it will read/write/send data outside the agent in ways you should explicitly consent to before use.

Purpose & Capability

The skill claims to convert images to short videos using a NemoVideo backend; the required NEMO_TOKEN and the documented API endpoints align with that purpose. Minor concern: the skill name includes 'Canva' which may be trademark confusion but not a technical mismatch. Also the registry summary earlier listed no config paths, while the SKILL.md frontmatter declares a config path (~/.config/nemovideo/), which is inconsistent.

Instruction Scope

The runtime instructions direct the agent to: read environment variable NEMO_TOKEN (or obtain an anonymous token by POSTing to a remote endpoint), detect install path(s) on disk (~/.clawhub, ~/.cursor/skills/) and read a config path (~/.config/nemovideo/), create sessions, and upload local files or URLs to the external API. Reading install/config paths and using arbitrary filesystem paths for uploads expands scope beyond simply 'accept images from the user' and could expose other local files if misused.

Install Mechanism

This is an instruction-only skill with no install spec or bundled code, so nothing will be written to disk by an installer. That lowers risk compared to downloadable installers.

Credentials

The skill requests a single credential (NEMO_TOKEN), which is proportionate to calling a third‑party rendering API. However, the SKILL.md will attempt to mint an anonymous token if none is present and the frontmatter references a config path that the registry metadata did not list — an inconsistency. Consider whether you want the agent to automatically obtain credentials for this external service.

Persistence & Privilege

The skill does not request always:true and contains no install-time hooks. Model invocation is allowed (platform default) but that is not, by itself, a red flag. Still, autonomous invocation combined with file upload/network I/O increases blast radius, so exercise caution.

What to consider before installing

This skill will upload images and session data to https://mega-api-prod.nemovideo.ai and may read your install/config paths to set attribution headers. Before installing or invoking it: (1) confirm you trust the nemovideo.ai service and are comfortable uploading any images (do not upload sensitive or private photos); (2) be aware the agent can auto-generate an anonymous token if NEMO_TOKEN is not set (it will contact an external endpoint); (3) note the SKILL.md frontmatter references a config path (~/.config/nemovideo/) and will detect install locations — if you prefer to avoid any filesystem probing, do not install; (4) test with non-sensitive images first; (5) prefer installing only if you can verify the skill’s source or provider (no homepage/source is listed here). If you need higher assurance, ask the skill author for source code or official documentation and a privacy policy explaining how uploads and tokens are handled.

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 images into a short"

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 — Convert Images into Video Clips

Send me your still 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 three product photos or a single illustration, type "turn my images into a short animated video with transitions and music", and you'll get a 1080p MP4 back in roughly 30-60 seconds. All rendering happens server-side.

Worth noting: using fewer images with high contrast produces smoother transitions.

Matching Input to Actions

User prompts referencing ai image to video canva, 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.

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

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

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

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.

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 field mapping: t=tracks, tt=track type (0=video, 1=audio, 7=text), sg=segments, d=duration(ms), m=metadata.

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

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "turn my images into a short animated video with transitions and music" — 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 social platforms.

Common Workflows

Quick edit: Upload → "turn my images into a short animated 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.