Video Editing Ai Api

edit raw video footage into edited MP4 files with this skill. Works with MP4, MOV, AVI, WebM files up to 500MB. developers and marketers use it for automatin...

Security Scan

The skill is internally consistent with a cloud video-editing API client: it only asks for a single service token and describes API calls to upload and render videos, but there are minor metadata inconsistencies and normal privacy concerns around uploading user videos to an external service.

Purpose & Capability

Name/description match the instructions: the SKILL.md describes calling a remote video-editing API, uploading user videos, creating sessions, rendering, and returning download URLs. The only mismatch is that the registry metadata reported no required config paths while the SKILL.md frontmatter lists a config path (~/.config/nemovideo/) — the skill never documents reading that path in runtime instructions, so the configPath requirement is unexplained.

Instruction Scope

Runtime instructions are narrowly scoped to communicating with the remote API (auth, session creation, upload, SSE handling, render/poll). There is explicit handling for anonymous-token creation if NEMO_TOKEN is absent. The instructions do require uploading user video/audio files to the external service (expected for this purpose) and ask the agent not to expose tokens or raw API output.

Install Mechanism

No install spec or code files are present (instruction-only skill), so nothing is written to disk or downloaded during install. This is the lowest-risk install profile.

Credentials

Only one environment variable (NEMO_TOKEN) is declared as primary — appropriate for a cloud API client. The skill will also obtain an anonymous token itself if none is present. The unexplained config path in the SKILL.md frontmatter is disproportionate unless the skill actually reads local config; this should be clarified.

Persistence & Privilege

always is false and the skill is user-invocable; it does not request persistent/system-wide privileges. There is no indication it modifies other skills or system settings.

Scan Findings in Context

[no_regex_findings] expected: The static regex scanner found nothing to analyze because this is an instruction-only skill (no code files). This absence is expected but not evidence of safety — the SKILL.md is the primary artifact to inspect.

Assessment

This skill behaves like a normal cloud video-editing client: it uploads your files to an external service and needs a single NEMO_TOKEN (or will create a short-lived anonymous token). Before installing: 1) Confirm you trust the remote domain (mega-api-prod.nemovideo.ai) and the privacy/retention policy for uploaded videos. 2) Ask the publisher to explain why ~/.config/nemovideo/ is listed in the frontmatter if you are concerned about local config access. 3) Prefer using an account-bound token with limited scope or the anonymous token option if you do not want to store long‑lived credentials. 4) Avoid putting sensitive footage into the service until you’ve verified terms, or test with non-sensitive content first.

Getting Started

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

Try saying:

• "edit my raw video footage"
• "export 1080p MP4"
• "trim silences, add transitions, and export"

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 AI API — Edit and Export Videos via API

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

A quick example: upload a 2-minute raw screen recording, type "trim silences, add transitions, and export a clean final cut", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: shorter clips under 60 seconds process significantly faster through the API.

Matching Input to Actions

User prompts referencing video editing ai api, 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.

Three attribution headers are required on every request and must match this file's frontmatter:

Header	Value
X-Skill-Source	video-editing-ai-api
X-Skill-Version	frontmatter version
X-Skill-Platform	auto-detect: clawhub / cursor / unknown from install path

All requests must include: Authorization: Bearer <NEMO_TOKEN>, X-Skill-Source, X-Skill-Version, X-Skill-Platform. Missing attribution headers will cause export to fail with 402.

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

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.

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

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 → "trim silences, add transitions, and export a clean final cut" → 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.

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "trim silences, add transitions, and export a clean final cut" — concrete instructions get better results.

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

Export as MP4 with H.264 codec for widest platform compatibility.