Cinematic Video

Turn a 2-minute handheld smartphone clip into 4K cinematic MP4 video just by typing what you need. Whether it's transforming everyday footage into film-quali...

Security Scan

The skill's instructions and required credential (NEMO_TOKEN) align with its stated purpose (cloud video processing), but it will upload your raw videos to a third-party service and can auto-provision temporary tokens—so review privacy and trust before use.

Purpose & Capability

Name/description match the actions in SKILL.md: the skill talks to a remote nemovideo.ai API to process and export videos. Requested credential (NEMO_TOKEN) is appropriate for that service. Minor inconsistency: the registry metadata listed no required config paths, but the SKILL.md frontmatter references a config path (~/.config/nemovideo/).

Instruction Scope

The runtime instructions require uploading user-supplied video/audio/image files to https://mega-api-prod.nemovideo.ai and polling/rendering there. If NEMO_TOKEN is not present, the skill instructs the agent to request an anonymous token from the service (auto-provisioning). Both behaviors are coherent for cloud processing but have clear privacy implications (user data leaves the local environment) and the agent will perform network calls and token requests without additional user interaction unless the front-end prevents it.

Install Mechanism

No install spec and no code files—this is an instruction-only skill. That lowers risk from filesystem installation or arbitrary code fetches.

Credentials

Only one credential is declared (NEMO_TOKEN), which fits the service integration. The SKILL.md additionally documents that a token can be obtained anonymously via the auth endpoint. The skill also expects to add attribution headers (X-Skill-Source, X-Skill-Version, X-Skill-Platform) which may reveal install-path/platform metadata; this is not necessary for functionality and is a minor privacy leak.

Persistence & Privilege

always is false and there is no install or system modification. The skill stores session IDs server-side for job tracking (normal for render services). It does not request elevated or persistent system privileges.

Assessment

This skill appears to be what it claims: it sends your uploaded videos to a nemovideo.ai backend to produce cinematic exports and uses a NEMO_TOKEN (which it can also auto-provision as a temporary anonymous token). Before installing or using it: - Be aware that any video/audio/image you upload will be transmitted to and processed by an external service (mega-api-prod.nemovideo.ai). Don't upload sensitive or private footage unless you trust the service. - You can provide your own NEMO_TOKEN to avoid automatic anonymous token creation; otherwise the skill will request a temporary token on your behalf (100 free credits, 7-day expiry according to the docs). - Note the small metadata mismatch (SKILL.md references a config path not declared in registry metadata) and that attribution headers may disclose platform/install-path info—this is a privacy consideration, not a functional blocker. - There is no code installed locally (instruction-only), but the skill will make network calls; verify that the domain is legitimate for your use case and check the service's terms/privacy if you need guarantees about retention and deletion of uploaded media. If you need higher assurance, ask the skill author/provider for a homepage, privacy policy, or a known publisher identity before sending real user content.

Getting Started

Share your raw video footage and I'll get started on AI cinematic enhancement. Or just tell me what you're thinking.

Try saying:

• "transform my raw video footage"
• "export 4K MP4"
• "make this look cinematic with color"

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.

Cinematic Video — Transform Footage into Film-Quality Video

Drop your raw video footage in the chat and tell me what you need. I'll handle the AI cinematic enhancement on cloud GPUs — you don't need anything installed locally.

Here's a typical use: you send a a 2-minute handheld smartphone clip, ask for make this look cinematic with color grading, letterbox bars, and smooth transitions, and about 1-2 minutes later you've got a MP4 file ready to download. The whole thing runs at 4K by default.

One thing worth knowing — clips under 60 seconds render faster and give the AI more consistent color grading results.

Matching Input to Actions

User prompts referencing cinematic video, 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.

Base URL: https://mega-api-prod.nemovideo.ai

Endpoint	Method	Purpose
/api/tasks/me/with-session/nemo_agent	POST	Start a new editing session. Body: {"task_name":"project","language":"<lang>"}. Returns session_id.
/run_sse	POST	Send a user message. Body includes app_name, session_id, new_message. Stream response with Accept: text/event-stream. Timeout: 15 min.
/api/upload-video/nemo_agent/me/<sid>	POST	Upload a file (multipart) or URL.
/api/credits/balance/simple	GET	Check remaining credits (available, frozen, total).
/api/state/nemo_agent/me/<sid>/latest	GET	Fetch current timeline state (draft, video_infos, generated_media).
/api/render/proxy/lambda	POST	Start export. Body: {"id":"render_<ts>","sessionId":"<sid>","draft":<json>,"output":{"format":"mp4","quality":"high"}}. Poll status every 30s.

Accepted file types: mp4, mov, avi, webm, mkv, jpg, png, gif, webp, mp3, wav, m4a, aac.

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

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

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

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 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)

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "make this look cinematic with color grading, letterbox bars, and smooth transitions" — concrete instructions get better results.

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

Export as MP4 with H.264 codec for the best balance of cinematic quality and file size.

Common Workflows

Quick edit: Upload → "make this look cinematic with color grading, letterbox bars, and smooth 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.