Video Editing Maker Free

Get edited MP4 videos ready to post, without touching a single slider. Upload your raw video clips (MP4, MOV, AVI, WebM, up to 500MB), say something like "tr...

Security Scan

The skill's instructions are mostly consistent with a remote AI video-editing backend, but there are small inconsistencies (metadata vs SKILL.md), an unknown source, and it asks to create/store an auth token and contact an external service — so verify before installing.

Purpose & Capability

Name and description match the runtime instructions (upload clips, start sessions, render on cloud GPU). Requesting a NEMO_TOKEN is coherent for an external API. However, the SKILL.md frontmatter declares a config path (~/.config/nemovideo/) while the registry metadata lists no config paths — this mismatch should be clarified.

Instruction Scope

Instructions are narrowly focused on sending clips to the listed nemovideo.ai endpoints, obtaining an anonymous token if none is present, creating sessions, uploading files, and polling render status. They do instruct generation and storing of a token (NEMO_TOKEN) and require certain attribution headers. The skill does not request arbitrary file reads in the provided excerpt, but references platform-detection from the install path and a local config folder which could imply reading/writing ~/.config/nemovideo/ — that is not shown explicitly and should be confirmed.

Install Mechanism

Instruction-only skill with no install spec and no code files; nothing is written to disk by the skill itself as packaged here. This is the lowest-risk install mechanism in isolation.

Credentials

Only one credential is declared (NEMO_TOKEN), which fits the API usage. The SKILL.md also describes generating an anonymous token and storing it as NEMO_TOKEN; storing credentials in environment variables is common but you should confirm where/how long the token will be stored. The implicit reference to a local config path (~/.config/nemovideo/) in SKILL.md metadata is not reflected in the registry fields and could grant the skill access to local config if implemented — this should be clarified.

Persistence & Privilege

always:false and model invocation is allowed (default). The skill does not request permanent platform-wide privileges. There is no evidence it modifies other skills or system-wide settings.

What to consider before installing

This skill appears to call a third-party API (mega-api-prod.nemovideo.ai) to do remote video editing and will use or create a NEMO_TOKEN. Before installing: 1) Confirm you trust the external domain and service operator (source/homepage unknown). 2) Ask the publisher to clarify the config path usage (~/.config/nemovideo/) and whether the skill will read/write files there. 3) Understand what happens to uploaded videos (retention, privacy, deletion policy) and whether uploads leave copies on the provider. 4) Decide whether you want the skill to create and store an anonymous token as an environment variable (NEMO_TOKEN); prefer ephemeral tokens or explicit consent for persistent storage. 5) Be aware the skill adds attribution headers (it may reveal that you’re using this skill and the install platform). If any of these points are unacceptable or unanswered, do not install or run the skill with sensitive videos or on sensitive systems.

Getting Started

Got raw video clips to work with? Send it over and tell me what you need — I'll take care of the AI video editing.

Try saying:

• "edit a 2-minute unedited phone recording into a 1080p MP4"
• "trim the footage, add transitions, and export a clean final video"
• "editing and assembling raw clips into a finished video without paid software for casual creators and students"

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 Editing Maker Free — Edit and Export Finished Videos

Send me your raw video clips 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 unedited phone recording, type "trim the footage, add transitions, and export a clean final video", 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.

Matching Input to Actions

User prompts referencing video editing maker free, 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-maker-free
X-Skill-Version	frontmatter version
X-Skill-Platform	auto-detect: clawhub / cursor / unknown from install path

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 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 the footage, add transitions, and export a clean final video" → 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 the footage, add transitions, and export a clean final 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.