Video Editor Hourly Rate

edit raw footage into polished edited clips with this skill. Works with MP4, MOV, AVI, WebM files up to 500MB. freelancers and small business owners use it f...

Security Scan

The skill's behavior largely matches a cloud video-editing integration, but there are small inconsistencies and external-network/privacy considerations you should be aware of before installing.

Purpose & Capability

The skill's name/description (AI cloud video editing) lines up with the endpoints and the single required credential (NEMO_TOKEN). However the SKILL.md frontmatter declares a config path (~/.config/nemovideo/) while the registry metadata showed no required config paths — this mismatch is unexplained and worth clarifying.

Instruction Scope

Runtime instructions are focused on uploading video, starting sessions, streaming SSE edits, checking credit balance, and starting exports — all coherent with an online video-editing service. The skill instructs generating an anonymous token if no env var is present and to save session_id; it does not ask to read unrelated system files or other credentials.

Install Mechanism

There is no install spec and no code files; the skill is instruction-only, so nothing is written to disk by an installer. This is the lowest-risk install footprint.

Credentials

Only one credential is declared (NEMO_TOKEN), which is appropriate for a third‑party API. The frontmatter's mention of a config path (~/.config/nemovideo/) could imply reading local config files for tokens — acceptable for convenience but it wasn't listed in the registry summary, creating an unexplained discrepancy.

Persistence & Privilege

The skill does not request 'always: true' and does not indicate modifying other skills or system settings. It does instruct the agent to store a session_id and use a token for API calls, which is normal for a session-oriented remote API.

What to consider before installing

This skill appears to be an instruction-only connector to a cloud video-editing service and needs a NEMO_TOKEN (or it will obtain a short-lived anonymous token) and will upload your media to mega-api-prod.nemovideo.ai. Before installing, consider: 1) confirm you trust nemovideo.ai (privacy of uploaded footage matters); 2) clarify the config-path discrepancy (~/.config/nemovideo/ is mentioned in the frontmatter but not in registry metadata) — find out whether the skill will read or write files there; 3) if you prefer tighter control, set a NEMO_TOKEN yourself (or use a limited/throwaway token) rather than letting the skill request an anonymous token; 4) check data retention and terms on the service (how long media and drafts are stored, who can access them); and 5) if you need strict confidentiality, avoid uploading sensitive footage to an unfamiliar third party. If you want me to attempt contacting the skill author or to extract the exact frontmatter fields for further checks, say so.

Getting Started

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

Try saying:

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

Automatic Setup

On first interaction, connect to the processing API before doing anything else. Show a brief status like "Setting things up...".

Token: If NEMO_TOKEN environment variable is already set, use it and skip to Session below.

Free token: Generate a UUID as client identifier, then POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id: <uuid>. The response field data.token becomes your NEMO_TOKEN (100 credits, 7-day expiry).

Session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Save session_id from the response.

Confirm to the user you're connected and ready. Don't print tokens or raw JSON.

Video Editor Hourly Rate — Edit Videos Without Hourly Fees

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

Here's a typical use: you send a a 3-minute interview recording, ask for trim pauses, add transitions, and export a clean final cut, and about 1-2 minutes 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 2 minutes process fastest and cost fewer credits.

Matching Input to Actions

User prompts referencing video editor hourly rate, 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-editor-hourly-rate
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 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

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 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 pauses, 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 pauses, 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 for widest compatibility across platforms and devices.