Video Editing With Figma

Get exported video files ready to post, without touching a single slider. Upload your design assets, video clips (MP4, MOV, PNG, WebM, up to 500MB), say some...

Security Scan

The skill's requirements and runtime instructions are coherent with its stated purpose (uploading assets to a NemoVideo cloud service to produce videos); it requests a single API token and has no install steps or unrelated credentials.

Purpose & Capability

The skill is a Figma-to-video cloud front-end: requiring an API token (NEMO_TOKEN) and describing session, upload, render, and export endpoints is consistent with that purpose. It does not ask for unrelated cloud credentials or system-level access.

Instruction Scope

Instructions describe network calls to mega-api-prod.nemovideo.ai, session creation, SSE handling, and multipart uploads — all expected for a cloud render pipeline. The skill also instructs deriving attribution headers from its frontmatter and detecting an install path to set X-Skill-Platform; this implies the agent may read its own metadata and possibly probe install paths. That's reasonable for attribution but worth noting because it requires filesystem and network access.

Install Mechanism

This is an instruction-only skill with no install spec and no code files, so nothing will be downloaded or written to disk by an installer step.

Credentials

Only NEMO_TOKEN is declared as required, which matches the API usage. The instructions also include logic to obtain an anonymous token from the backend if NEMO_TOKEN is absent (POST to /api/auth/anonymous-token). The SKILL.md frontmatter lists a config path (~/.config/nemovideo/) for attribution/storage, which is a minor inconsistency with registry metadata that listed no required config paths — functionally harmless but worth being aware of.

Persistence & Privilege

The skill does not request always:true and is user-invocable; it can run autonomously (default) but does not claim elevated or system-wide privileges. There is no indication it will modify other skills or global agent settings.

Assessment

This skill uploads files you provide to a NemoVideo cloud service and will use a NEMO_TOKEN if you supply one; otherwise it will request an anonymous token from the service. Before installing/using it: (1) confirm you are comfortable uploading your design and video files to mega-api-prod.nemovideo.ai and review that service's privacy/terms; (2) understand that providing a persistent NEMO_TOKEN gives the skill API-level access to that account (don't reuse highly privileged or unrelated tokens); (3) if you prefer not to create an anonymous account, set NEMO_TOKEN yourself or avoid using the auto-token flow; (4) note the skill may read its own metadata and probe common install paths to set attribution headers — this is normal attribution behavior but means the agent will access its environment and metadata.

Getting Started

Share your design assets, video clips and I'll get started on Figma-to-video conversion. Or just tell me what you're thinking.

Try saying:

• "convert my design assets, video clips"
• "export 1080p MP4"
• "convert my Figma design frames into"

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.

Video Editing with Figma — Convert Figma Designs to Video

This tool takes your design assets, video clips and runs Figma-to-video conversion through a cloud rendering pipeline. You upload, describe what you want, and download the result.

Say you have a Figma prototype with animated frames and transitions and want to convert my Figma design frames into a smooth product demo video with transitions — the backend processes it in about 1-2 minutes and hands you a 1080p MP4.

Tip: flatten complex components in Figma before exporting to avoid rendering issues.

Matching Input to Actions

User prompts referencing video editing with figma, 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.

Headers are derived from this file's YAML frontmatter. X-Skill-Source is video-editing-with-figma, 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).

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

Backend Response Translation

The backend assumes a GUI exists. Translate these into API actions:

Backend says	You do
"click [button]" / "点击"	Execute via API
"open [panel]" / "打开"	Query session state
"drag/drop" / "拖拽"	Send edit via SSE
"preview in timeline"	Show track summary
"Export button" / "导出"	Execute 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 "convert my Figma design frames into a smooth product demo video with transitions" — concrete instructions get better results.

Max file size is 500MB. Stick to MP4, MOV, PNG, WebM for the smoothest experience.

Export as MP4 for widest compatibility.

Common Workflows

Quick edit: Upload → "convert my Figma design frames into a smooth product demo video with transitions" → 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.