Video Editor Edimakor

edit raw video footage into edited MP4 clips with this skill. Works with MP4, MOV, AVI, WebM files up to 500MB. content creators use it for editing and polis...

Security Scan

The skill's requirements and runtime instructions are consistent with a cloud video-editing connector (it needs one API token and talks only to the nemo-video API), though there are a few minor metadata/instruction inconsistencies you should be aware of.

Purpose & Capability

Name/description match the runtime instructions: the SKILL.md describes uploading videos, creating render jobs, polling for results, and returning download URLs. Requesting a single service token (NEMO_TOKEN) is appropriate for a cloud video render service.

Instruction Scope

Instructions confine network activity to https://mega-api-prod.nemovideo.ai and describe uploading user video files, creating sessions, SSE for edits, and polling renders. They also instruct the agent to read this file's YAML frontmatter and detect the install path (to set X-Skill-Platform). Those filesystem reads are plausible for attribution headers but do require access to the agent's skill file and potentially home-directory paths.

Install Mechanism

No install spec or code files are present (instruction-only), so nothing is downloaded or written by the skill itself — lowest install risk.

Credentials

The skill requests only NEMO_TOKEN as the primary credential, which is proportional to a cloud API client. Minor inconsistency: registry metadata earlier listed no required config paths, while the SKILL.md frontmatter lists a config path (~/.config/nemovideo/). This mismatch is likely a metadata oversight but worth noting.

Persistence & Privilege

always is false and the skill does not request system-wide privileges or attempt to modify other skills or global settings. It may read local skill metadata and detect install path to populate attribution headers, which is reasonable.

Assessment

This skill appears to be a straightforward connector to a cloud video-editing API. Before installing: 1) Confirm you trust the domain https://mega-api-prod.nemovideo.ai and its privacy/TOS since your uploaded videos will be sent to that service. 2) Only provide NEMO_TOKEN if you expect the service to act on your behalf; if you don't have a token the skill will obtain a short-lived anonymous token automatically. 3) Be aware the skill will read its own frontmatter and may check common install/config paths in your home directory for attribution — avoid installing it on systems with sensitive files you don't want read. 4) Note the SKILL.md metadata mentions a config path (~/.config/nemovideo/) but registry metadata omitted it — treat this as a minor inconsistency and ask the publisher to clarify if you need stronger assurance. If you are uncomfortable with sending video content to an external service, do not install or invoke this skill.

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 the pauses, add background music,"

Getting Connected

Before handling any user request, establish a connection to the backend API. Show a brief status like "Connecting...".

If NEMO_TOKEN is in the environment, use it directly and create a session. Otherwise, acquire a free starter token:

• Generate a UUID as client identifier
• POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with the X-Client-Id header
• The response includes a token with 100 free credits valid for 7 days — use it as NEMO_TOKEN

Then create a session by POSTing to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer authorization and body {"task_name":"project","language":"en"}. The session_id in the response is needed for all following requests.

Tell the user you're ready. Keep the technical details out of the chat.

Video Editor Edimakor — Edit and Export Polished Videos

Drop your raw video 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 2-minute unedited screen recording, ask for trim the pauses, add background music, and export as MP4, 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 60 seconds process significantly faster.

Matching Input to Actions

User prompts referencing video editor edimakor, 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-editor-edimakor
• 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

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 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 "trim the pauses, add background music, and export as MP4" — 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.

Common Workflows

Quick edit: Upload → "trim the pauses, add background music, and export as MP4" → 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.