Free Free Editor

Skip the learning curve of professional editing software. Describe what you want — trim the pauses, add transitions, and export a clean final cut — and get e...

Security Scan

The skill's requests and runtime instructions are consistent with a cloud video-editing integration; nothing requested is disproportionate to that purpose, though there are a few minor documentation/inventory inconsistencies to be aware of.

Purpose & Capability

Name/description (cloud AI video editing) lines up with required credential (NEMO_TOKEN), API endpoints, and upload/export actions described in SKILL.md. The declared config path (~/.config/nemovideo/) is plausible for a video-service client.

Instruction Scope

Instructions focus exclusively on creating a session, uploading media, streaming SSE, checking credits/state, and starting renders on the external nemo API — all within the stated editing purpose. Note: SKILL.md instructs hiding technical details from the chat and requires attribution headers; it also describes an anonymous-token fallback flow (see environment_proportionality). There are no instructions to read unrelated local files or other credentials.

Install Mechanism

Instruction-only skill with no install spec or code files. This is low-risk from an install/extraction standpoint because nothing is written or executed locally by the skill package itself.

Credentials

Only one credential is declared (NEMO_TOKEN) which is reasonable for a hosted editing API. However, the SKILL.md also documents an anonymous-token acquisition flow (POST to /anonymous-token) if NEMO_TOKEN is absent, so declaring NEMO_TOKEN as strictly required is inconsistent. The metadata also lists a config path (~/.config/nemovideo/); SKILL.md does not explicitly instruct reading it, but its presence suggests the skill may look for local config if implemented — consider whether you want local config access. The NEMO_TOKEN (or anonymous token) will be sent as a bearer token to mega-api-prod.nemovideo.ai when making requests.

Persistence & Privilege

The skill is not always-enabled and can be invoked by the user only. There is no install step that modifies other skills or system-wide settings in the package as provided.

Assessment

This instruction-only skill appears to do what it says: it uploads your media to a cloud service (mega-api-prod.nemovideo.ai) and uses a bearer token (NEMO_TOKEN) or an anonymously minted token to run edits and return a download URL. Before installing/using: 1) Understand that any token you provide will be sent to that external service and that your video files will be uploaded — don’t upload sensitive or private videos unless you trust the service and have reviewed its privacy/terms. 2) If you don’t want to supply a persistent token, use the anonymous flow described (it gives limited temporary credits). 3) Note the minor inconsistency: the package declares NEMO_TOKEN as required but the runtime supports anonymous tokens as a fallback. 4) Because this is instruction-only, there is no bundled code to inspect; if you require stronger assurances, ask the publisher for an official homepage, privacy policy, or an implementation that can be code-reviewed before use.

Getting Started

Ready when you are. Drop your raw video clips here or describe what you want to make.

Try saying:

• "edit a 2-minute unedited screen recording into a 1080p MP4"
• "trim the pauses, add transitions, and export a clean final cut"
• "editing videos for free without paid software for content creators and students"

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.

Free Video Editor — Edit and Export Videos Free

This tool takes your raw video clips and runs AI video editing through a cloud rendering pipeline. You upload, describe what you want, and download the result.

Say you have a 2-minute unedited screen recording and want to trim the pauses, add transitions, and export a clean final cut — the backend processes it in about 1-2 minutes and hands you a 1080p MP4.

Tip: shorter clips under 3 minutes process significantly faster.

Matching Input to Actions

User prompts referencing free free editor, 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.

Headers are derived from this file's YAML frontmatter. X-Skill-Source is free-free-editor, X-Skill-Version comes from the version field, and X-Skill-Platform is detected from the install path (~/.clawhub/ = clawhub, ~/.cursor/skills/ = cursor, otherwise unknown).

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 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)

Common Workflows

Quick edit: Upload → "trim the 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 the 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.