Ai Paid Content Generator

Skip the learning curve of professional editing software. Describe what you want — turn this clip into a polished paid course intro with captions and brandin...

Security Scan

The skill's purpose (remote video editing) matches most runtime instructions, but there are several inconsistencies about required environment/config access and a small amount of scope creep that warrant caution before installing.

Purpose & Capability

The skill claims to be a remote video editing/export service and all API endpoints in SKILL.md align with that purpose. However, the registry metadata declares a required env var (NEMO_TOKEN) and a config path (~/.config/nemovideo/) while the instructions explicitly describe obtaining an anonymous token via the service API when NEMO_TOKEN is not present. Declaring the token as 'required' while documenting an automatic anonymous-token flow is inconsistent and unexplained.

Instruction Scope

The SKILL.md instructs the agent to upload user media to a third-party backend, create/persist session IDs, and stream SSE responses — all reasonable for a cloud render pipeline. Two items stand out: (1) instructions tell the agent to detect the agent's install path (e.g., ~/.clawhub/ or ~/.cursor/skills/) to set an X-Skill-Platform header, which implies reading local install paths; and (2) the frontmatter's declared configPaths are not otherwise referenced in the runtime steps. Both are scope expansions beyond pure media upload and editing.

Install Mechanism

This is an instruction-only skill with no install spec or code files, so nothing will be downloaded or written during install. That lowers the implementation risk.

Credentials

Only a single credential (NEMO_TOKEN) is declared, which is consistent with a remote API. However, the skill both declares NEMO_TOKEN as required and describes an anonymous-token acquisition flow (POST to /api/auth/anonymous-token) when NEMO_TOKEN is absent. The metadata also declares a config path (~/.config/nemovideo/) that the instructions never use. These mismatches make it unclear whether the agent must be given a persistent secret or can always operate with ephemeral anonymous tokens — an ambiguity that affects user privacy and credential handling.

Persistence & Privilege

always is false and the skill does not request system-wide modifications. It instructs storing session_id for the session lifecycle (normal). Autonomous invocation is allowed by default (platform standard) and is not combined with other high-risk factors here.

What to consider before installing

This skill will upload user video and audio files to a remote service (mega-api-prod.nemovideo.ai) for processing. Before installing, consider: 1) Privacy: uploaded media may contain sensitive or copyrighted material — check the service's privacy, retention, and ownership policies. 2) Credentials: the metadata requires NEMO_TOKEN but the instructions say the agent can obtain an anonymous token; do not set a long-lived NEMO_TOKEN unless you trust the service and understand what it grants. 3) Local access: the skill asks the agent to detect its install path to set an attribution header and lists a config path in metadata — confirm whether the skill will read local filesystem paths and why. 4) Billing/credits: the anonymous token gives limited free credits for a short period; understand what happens when credits run out or if the account is bound after registration. If you need higher assurance, ask the publisher for source code or an official homepage, or request clarification on why NEMO_TOKEN and ~/.config/nemovideo/ are declared required when the runtime flow can create anonymous tokens.

Getting Started

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

Try saying:

• "generate my raw video footage"
• "export 1080p MP4"
• "turn this clip into a polished"

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.

AI Paid Content Generator — Generate and Export Monetizable Videos

Send me your raw video footage and describe the result you want. The AI monetizable content creation runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload a 3-minute talking-head recording, type "turn this clip into a polished paid course intro with captions and branding", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: keep source clips under 5 minutes for faster processing and cleaner AI output.

Matching Input to Actions

User prompts referencing ai paid content generator, 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.

Skill attribution — read from this file's YAML frontmatter at runtime:

• X-Skill-Source: ai-paid-content-generator
• X-Skill-Version: from frontmatter version
• X-Skill-Platform: detect from install path (~/.clawhub/ → clawhub, ~/.cursor/skills/ → cursor, else unknown)

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

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 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 → "turn this clip into a polished paid course intro with captions and branding" → 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 "turn this clip into a polished paid course intro with captions and branding" — 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 course platforms like Teachable and Gumroad.