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dsewell-583h0

Jpeng Video

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 jpeng-video
功能描述
convert raw video footage into compressed MP4 files with this skill. Works with MP4, MOV, AVI, WebM files up to 500MB. content creators use it for compressin...
使用说明 (SKILL.md)

Getting Started

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

Try saying:

  • "convert my raw video footage"
  • "export 1080p MP4"
  • "compress this video to a smaller"

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.

JPEG Video — Compress and Export Video Files

Drop your raw video footage in the chat and tell me what you need. I'll handle the AI video compression on cloud GPUs — you don't need anything installed locally.

Here's a typical use: you send a a 2-minute 4K phone recording, ask for compress this video to a smaller file size without losing quality, and about 30-90 seconds later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.

One thing worth knowing — shorter clips compress faster and give more predictable output sizes.

Matching Input to Actions

User prompts referencing jpeng video, 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.

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

  • X-Skill-Source: jpeng-video
  • X-Skill-Version: from frontmatter version
  • X-Skill-Platform: detect from install path (~/.clawhub/clawhub, ~/.cursor/skills/cursor, else unknown)

Include Authorization: Bearer \x3CNEMO_TOKEN> and all attribution headers on every request — omitting them triggers a 402 on export.

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)

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

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.

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

Common Workflows

Quick edit: Upload → "compress this video to a smaller file size without losing quality" → Download MP4. Takes 30-90 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 "compress this video to a smaller file size without losing quality" — concrete instructions get better results.

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

H.264 codec gives the best balance of quality and size.

安全使用建议
This skill appears to be a cloud-based video compressor that uploads your files to mega-api-prod.nemovideo.ai and uses a single API token (NEMO_TOKEN). Before installing or invoking it: (1) confirm you trust the nemovideo domain and its privacy policy — uploaded videos will leave your machine; (2) avoid sending sensitive or private footage unless you’ve verified the service; (3) verify the registry metadata vs. SKILL.md (SKILL.md mentions ~/.config/nemovideo/ and probing install paths) and ask the publisher why that path is needed; (4) be aware the skill will read its own frontmatter and check common directories to set attribution headers (these are modest filesystem reads but worth noting); (5) prefer providing an explicit, limited token for this service rather than sharing broader credentials. If you want higher assurance, request the skill's publisher/source code or ask them to remove the config-path and install-path probes.
功能分析
Type: OpenClaw Skill Name: jpeng-video Version: 1.0.0 The jpeng-video skill is a legitimate integration for video compression and editing services provided by nemovideo.ai. The SKILL.md file provides detailed instructions for the AI agent to manage authentication via tokens, handle session states, and interact with specific API endpoints at mega-api-prod.nemovideo.ai. There are no indicators of data exfiltration, unauthorized file access, or malicious execution; the requested environment variables and configuration paths are specific to the skill's functionality.
能力评估
Purpose & Capability
Name and description claim cloud video compression and the SKILL.md instructs use of a single service (mega-api-prod.nemovideo.ai) and a NEMO_TOKEN — that is coherent. However the SKILL.md metadata lists a config path (~/.config/nemovideo/) even though the registry metadata lists 'Required config paths: none', creating a mismatch between declared requirements and the runtime instructions.
Instruction Scope
Runtime instructions perform network operations (session creation, SSE chat, uploads, export polling) which are expected for a cloud render service, but they also instruct the agent to: read this file's YAML frontmatter at runtime, detect install path by probing user paths (~/.clawhub/, ~/.cursor/skills/) to set X-Skill-Platform, and reference a local config path in metadata. Those filesystem probes go beyond just uploading a user-supplied video and increase the skill's read-scope on the agent environment.
Install Mechanism
Instruction-only skill with no install spec and no code files — nothing is written to disk by an installer. This is the lowest install risk.
Credentials
The skill only requires a single credential (NEMO_TOKEN), which is appropriate for a third‑party API. The SKILL.md also describes obtaining an anonymous token via an API call if NEMO_TOKEN is not present. Still, the metadata/config-path mismatch (SKILL.md claims a config path but registry shows none) is unexplained and worth verifying.
Persistence & Privilege
always:false and normal autonomy settings. The skill does not request permanent 'always' presence or other skills' credentials, so it does not demand elevated persistence.
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 jpeng-video
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /jpeng-video 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
- Initial release of jpeng-video: compress and export video files to 1080p MP4 using cloud GPUs. - Supports MP4, MOV, AVI, and WebM files up to 500MB. - Fast cloud processing: typical jobs complete within 30–90 seconds. - Automatic handling of anonymous/free token authentication for easy onboarding. - Integrated error handling for session, credits, file size, and plan tier issues. - Requires NEMO_TOKEN; provides usage guidance and common workflows for content creators.
元数据
Slug jpeng-video
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

Jpeng Video 是什么?

convert raw video footage into compressed MP4 files with this skill. Works with MP4, MOV, AVI, WebM files up to 500MB. content creators use it for compressin... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 88 次。

如何安装 Jpeng Video?

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

Jpeng Video 是免费的吗?

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

Jpeng Video 支持哪些平台?

Jpeng Video 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 Jpeng Video?

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

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