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vcarolxhberger

Maker Pro

作者 vcarolxhberger · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install maker-pro
功能描述
create raw video footage into polished professional videos with this skill. Works with MP4, MOV, AVI, WebM files up to 500MB. content creators and marketers...
使用说明 (SKILL.md)

Getting Started

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

Try saying:

  • "create a 3-minute unedited screen recording or phone video into a 1080p MP4"
  • "cut the pauses, add intro music, and export as a polished professional video"
  • "turning raw footage into professional-grade edited videos for content creators and marketers"

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.

Maker Pro — Create and Export Professional Videos

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

A quick example: upload a 3-minute unedited screen recording or phone video, type "cut the pauses, add intro music, and export as a polished professional video", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: shorter clips under 2 minutes process significantly faster and give cleaner AI edits.

Matching Input to Actions

User prompts referencing maker pro, 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.

All calls go to https://mega-api-prod.nemovideo.ai. The main endpoints:

  1. SessionPOST /api/tasks/me/with-session/nemo_agent with {"task_name":"project","language":"\x3Clang>"}. Gives you a session_id.
  2. Chat (SSE)POST /run_sse with session_id and your message in new_message.parts[0].text. Set Accept: text/event-stream. Up to 15 min.
  3. UploadPOST /api/upload-video/nemo_agent/me/\x3Csid> — multipart file or JSON with URLs.
  4. CreditsGET /api/credits/balance/simple — returns available, frozen, total.
  5. StateGET /api/state/nemo_agent/me/\x3Csid>/latest — current draft and media info.
  6. ExportPOST /api/render/proxy/lambda with render ID and draft JSON. Poll GET /api/render/proxy/lambda/\x3Cid> every 30s for completed status and download URL.

Formats: 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-pro
X-Skill-Version frontmatter version
X-Skill-Platform auto-detect: clawhub / cursor / unknown from install path

All requests must include: Authorization: Bearer \x3CNEMO_TOKEN>, X-Skill-Source, X-Skill-Version, X-Skill-Platform. Missing attribution headers will cause export to fail with 402.

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)

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

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.

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=\x3Cid>, 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

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "cut the pauses, add intro music, and export as a polished professional video" — concrete instructions get better results.

Max file size is 500MB. Stick to MP4, MOV, AVI, WebM for the smoothest experience.

Export as MP4 with H.264 codec for the best balance of quality and file size.

Common Workflows

Quick edit: Upload → "cut the pauses, add intro music, and export as a polished professional 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.

安全使用建议
This skill appears to implement a cloud video-editing workflow (you upload raw video, rendering happens on nemovideo.ai, you get a download URL). Before installing or using it, consider: 1) Your videos will be uploaded to a third‑party service (https://mega-api-prod.nemovideo.ai) — do not upload sensitive or private footage unless you trust the service and understand its privacy policy. 2) If you don't provide NEMO_TOKEN, the skill will request an anonymous token itself and proceed — be aware it can still transmit your files. 3) There is an unexplained metadata mismatch: SKILL.md references a local config path (~/.config/nemovideo/) that the registry metadata does not list; confirm whether the skill will read local config files or tokens. 4) The skill requires specific attribution headers; this is likely benign but is unusual — verify the origin/maintainer (no homepage is provided). If you need stronger assurance, ask the publisher for a homepage or privacy policy, insist on using your own service token rather than anonymous issuance, and avoid sending sensitive videos until you verify the provider.
功能分析
Type: OpenClaw Skill Name: maker-pro Version: 1.0.0 The 'maker-pro' skill is a legitimate integration for a cloud-based video editing service hosted at mega-api-prod.nemovideo.ai. It facilitates video processing, state management, and rendering through a series of REST API calls and SSE streams. While it requests access to a specific environment variable (NEMO_TOKEN) and a local configuration directory (~/.config/nemovideo/), these are explicitly declared in the metadata and are consistent with the skill's stated purpose. There is no evidence of data exfiltration, unauthorized execution, or malicious prompt injection.
能力评估
Purpose & Capability
The name/description (remote video editing) aligns with the runtime instructions (upload video, request render, return download URL) and the single required credential NEMO_TOKEN is consistent with calling a third‑party API. However, the SKILL.md frontmatter lists a config path (~/.config/nemovideo/) while the registry metadata claims no required config paths — that mismatch is unexplained.
Instruction Scope
Instructions tell the agent to contact https://mega-api-prod.nemovideo.ai to: obtain anonymous tokens if NEMO_TOKEN is absent, create sessions, upload media, poll renders, and include attribution headers. Those network calls and file uploads are expected for a cloud editing service, but the skill also mandates specific attribution headers and references an on‑disk config path in its frontmatter (possible implicit access to ~/.config/nemovideo/). The SKILL.md does not explicitly explain reading that config path but the metadata suggests it may be used — this ambiguity increases risk because it could cause the agent to look for and use local credentials/config unexpectedly.
Install Mechanism
Instruction-only skill with no install spec and no bundled code files. This is low risk from a code‑delivery perspective: nothing will be written to disk by an installer step.
Credentials
Only one declared environment variable (NEMO_TOKEN), which is appropriate for a service that requires authentication. The skill instructs the agent to obtain an anonymous token on the user's behalf if NEMO_TOKEN is missing — this means it will still contact the remote API and can upload user files even without user-supplied credentials. The frontmatter's configPaths entry (present in SKILL.md but not in registry metadata) suggests possible access to ~/.config/nemovideo/, which is not justified elsewhere.
Persistence & Privilege
always is false and there are no install scripts or persistent modifications described. The skill can be invoked autonomously (the platform default) but it does not request elevated persistence or alter other skills' configs.
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 maker-pro
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /maker-pro 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
Maker Pro 1.0.0 — Initial Release - Launches professional video editing skill for creators and marketers. - Supports raw video uploads up to 500MB (MP4, MOV, AVI, WebM). - Processes videos into polished 1080p MP4s in 1–2 minutes on cloud GPUs. - Includes session management, credit tracking, and easy export workflows. - Detailed API and error handling for reliable cloud editing.
元数据
Slug maker-pro
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

Maker Pro 是什么?

create raw video footage into polished professional videos with this skill. Works with MP4, MOV, AVI, WebM files up to 500MB. content creators and marketers... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 69 次。

如何安装 Maker Pro?

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

Maker Pro 是免费的吗?

是的,Maker Pro 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Maker Pro 支持哪些平台?

Maker Pro 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 Maker Pro?

由 vcarolxhberger(@vcarolxhberger)开发并维护,当前版本 v1.0.0。

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