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Ai Paid Content Generator

作者 dsewell-583h0 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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当前安装
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在 OpenClaw 中安装
/install ai-paid-content-generator
功能描述
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...
使用说明 (SKILL.md)

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 \x3Ctoken>, Content-Type: application/json, and body {"task_name":"project","language":"\x3Cdetected>"}. 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":"\x3Clang>"}. 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/\x3Csid> POST Upload a file (multipart) or URL.
/api/credits/balance/simple GET Check remaining credits (available, frozen, total).
/api/state/nemo_agent/me/\x3Csid>/latest GET Fetch current timeline state (draft, video_infos, generated_media).
/api/render/proxy/lambda POST Start export. Body: {"id":"render_\x3Cts>","sessionId":"\x3Csid>","draft":\x3Cjson>,"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 \x3CNEMO_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=\x3Cid> (get \x3Cid> 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.

安全使用建议
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.
功能分析
Type: OpenClaw Skill Name: ai-paid-content-generator Version: 1.0.0 The ai-paid-content-generator skill is a legitimate integration for a cloud-based video editing service (nemovideo.ai). It facilitates video uploads, session management, and remote rendering via a series of API calls to mega-api-prod.nemovideo.ai. The SKILL.md instructions provide clear guidance for the agent to handle authentication, track credits, and manage the rendering pipeline without any indicators of malicious intent, data exfiltration of sensitive local files, or unauthorized execution.
能力评估
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.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install ai-paid-content-generator
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /ai-paid-content-generator 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
ai-paid-content-generator 1.0.0 - Initial release: generate, edit, and export monetizable video content from user-uploaded footage using AI. - Supports MP4, MOV, AVI, WebM uploads up to 500MB; processing completes in 1–2 minutes for short clips. - Simple onboarding with automatic backend connection and token management for 100 free credits. - Provides credits checking, timeline state preview, and export/download actions via user prompts. - Clear cloud render pipeline and error handling ensure smooth workflow for content creators and online course sellers.
元数据
Slug ai-paid-content-generator
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Ai Paid Content Generator 是什么?

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... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 110 次。

如何安装 Ai Paid Content Generator?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install ai-paid-content-generator」即可一键安装,无需额外配置。

Ai Paid Content Generator 是免费的吗?

是的,Ai Paid Content Generator 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Ai Paid Content Generator 支持哪些平台?

Ai Paid Content Generator 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Ai Paid Content Generator?

由 dsewell-583h0(@dsewell-583h0)开发并维护,当前版本 v1.0.0。

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