Video Effects

Skip the learning curve of professional editing software. Describe what you want — add a cinematic color grade and motion blur to my video — and get effects-...

Security Scan

The skill's requirements and runtime instructions are consistent with a cloud-based video effects service; nothing requested appears disproportionate to that purpose.

Purpose & Capability

Name/description (cloud video effects) align with the single declared credential (NEMO_TOKEN) and the documented API endpoints for uploading, rendering, and exporting video.

Instruction Scope

Runtime instructions direct the agent to obtain or use a bearer token, create a session, upload user video files (multipart or URL), post SSE messages, poll render status, and return download URLs — all appropriate for a cloud render service. Note: the SKILL.md also instructs detecting an agent install path (~/.clawhub or ~/.cursor/skills/) and reading/writing a config directory (~/.config/nemovideo/) for attribution and token/session storage; reading/writing these local paths is outside the service API but is explained as attribution/token storage.

Install Mechanism

Instruction-only skill with no install spec and no code files — lowest install risk. All runtime behavior is API calls; nothing is downloaded or installed by the skill itself.

Credentials

Only NEMO_TOKEN is required (declared as primaryEnv), which fits a service that needs a bearer token. Small inconsistency: registry metadata reports no required config paths, while SKILL.md frontmatter lists ~/.config/nemovideo/ for storing tokens/session info — the skill may read/write that path even though it wasn't declared in the registry entry.

Persistence & Privilege

always is false and the skill does not request system-wide privileges or to modify other skills. It will create short-lived anonymous tokens and sessions and may store them in a per-skill config path; this is within expected behavior for a cloud service integration.

Assessment

This skill appears to do what it says: it will contact mega-api-prod.nemovideo.ai, obtain or use a bearer token (NEMO_TOKEN), and upload your video files for cloud rendering. Before installing/using it, consider: (1) Trust the service domain — videos you upload go to that third-party API; avoid uploading sensitive content. (2) The skill may auto-generate and store an anonymous token and session (SKILL.md references ~/.config/nemovideo/) even though registry metadata did not declare that path — verify where tokens/sessions are stored and remove them if desired. (3) You can pre-provide your own NEMO_TOKEN instead of allowing the skill to generate one. (4) Because the skill uploads local files, only use it when you intend to send the video off-device. If you need more assurance, ask the skill author for a privacy/data-retention statement or run the integration against a non-sensitive test clip first.

Getting Started

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

Try saying:

• "add my video clips"
• "export 1080p MP4"
• "add a cinematic color grade and"

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.

Video Effects — Apply Effects and Export Video

Drop your video clips in the chat and tell me what you need. I'll handle the AI effects application on cloud GPUs — you don't need anything installed locally.

Here's a typical use: you send a a 30-second clip filmed on a smartphone, ask for add a cinematic color grade and motion blur to my video, 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 — shorter clips under 60 seconds render effects noticeably faster.

Matching Input to Actions

User prompts referencing video effects, 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: video-effects
• 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 Handling

Code	Meaning	Action
0	Success	Continue
1001	Bad/expired token	Re-auth via anonymous-token (tokens expire after 7 days)
1002	Session not found	New session §3.0
2001	No credits	Anonymous: show registration URL with ?bind=<id> (get <id> from create-session or state response when needed). Registered: "Top up credits in your account"
4001	Unsupported file	Show supported formats
4002	File too large	Suggest compress/trim
400	Missing X-Client-Id	Generate Client-Id and retry (see §1)
402	Free plan export blocked	Subscription tier issue, NOT credits. "Register or upgrade your plan to unlock export."
429	Rate limit (1 token/client/7 days)	Retry in 30s 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

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)

Common Workflows

Quick edit: Upload → "add a cinematic color grade and motion blur to my video" → 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.

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "add a cinematic color grade and motion blur to my video" — concrete instructions get better results.

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

Export as MP4 for widest compatibility across platforms and devices.