Maker Free Capcut

Turn a 60-second smartphone video clip into 1080p watermark-free videos just by typing what you need. Whether it's editing and exporting videos without a wat...

Security Scan

The skill's behavior (calling a nemovideo cloud API to edit videos) mostly matches its description, but there are inconsistencies in the declared requirements (env/config) and no provenance/homepage for the service — these mismatches merit caution before installing or handing over credentials or uploads.

Purpose & Capability

Functionality described (server-side video editing/export) aligns with the runtime instructions which call nemovideo.ai endpoints and require a session token. However the registry metadata vs SKILL.md disagree: registry lists no config paths while the SKILL.md frontmatter declares a config path (~/.config/nemovideo/). That mismatch is unexplained and reduces trust in the manifest accuracy.

Instruction Scope

SKILL.md is an instruction-only skill that confines activity to network calls to the service (session creation, upload, SSE, render requests). It does not instruct reading unrelated system files or additional credentials. It instructs anonymous-token creation if NEMO_TOKEN is absent, and to keep session_id for operations.

Install Mechanism

No install spec or additional binaries — the skill is instruction-only and does not write code or download executables, which is a lower-risk installation surface.

Credentials

The skill declares a single primary credential (NEMO_TOKEN), which is reasonable for a cloud editing service. But the registry metadata listed NEMO_TOKEN as required while SKILL.md explicitly describes generating an anonymous NEMO_TOKEN if none is provided. Also the frontmatter lists a config path not present in the registry summary and not used explicitly in instructions. These inconsistencies make it unclear whether providing a persistent NEMO_TOKEN is required or optional.

Persistence & Privilege

always:false and no requests to modify other skills or global agent settings. The skill can be invoked autonomously (default), which is normal; there is no 'always' privilege or self-elevating install behavior described.

What to consider before installing

This skill connects to a third-party service (mega-api-prod.nemovideo.ai) to upload and process videos. Before installing: 1) Note the manifest inconsistencies — registry metadata, frontmatter, and SKILL.md disagree about config paths and whether NEMO_TOKEN is required. Treat that as a sign the publisher's packaging may be sloppy. 2) The skill will upload your raw videos to the remote service — do not send sensitive or private videos unless you trust the provider and its privacy/retention policy. 3) Prefer using the anonymous token flow (described in SKILL.md) rather than placing long-lived secrets in your environment; if you must provide NEMO_TOKEN, ensure it is scoped and revocable. 4) Because the skill's source/homepage is unknown, look for an official vendor page or contact before providing credentials or business-sensitive content. 5) If you proceed, monitor network activity and audit the service account/credits used for unexpected usage and revoke the token if you see suspicious behavior.

Getting Started

Send me your raw video clips and I'll handle the AI video editing. Or just describe what you're after.

Try saying:

• "create a 60-second smartphone video clip into a 1080p MP4"
• "cut the video, add music, and export without a watermark"
• "editing and exporting videos without a watermark like CapCut for TikTok creators"

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.

Maker Free CapCut — Edit and Export Watermark-Free 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 60-second smartphone video clip, type "cut the video, add music, and export without a watermark", and you'll get a 1080p MP4 back in roughly 30-60 seconds. All rendering happens server-side.

Worth noting: keeping clips under 2 minutes speeds up processing significantly.

Matching Input to Actions

User prompts referencing maker free capcut, 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	maker-free-capcut
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 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.

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 → "cut the video, add music, and export without a watermark" → Download MP4. Takes 30-60 seconds 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 "cut the video, add music, and export without a watermark" — 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 social platforms.