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Video Maker Linkedin

作者 vynbosserman65 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install video-maker-linkedin
功能描述
Turn a 60-second screen recording or three headshot photos into 1080p LinkedIn-ready videos just by typing what you need. Whether it's creating professional...
使用说明 (SKILL.md)

Getting Started

Got video clips or images to work with? Send it over and tell me what you need — I'll take care of the AI video creation.

Try saying:

  • "create a 60-second screen recording or three headshot photos into a 1080p MP4"
  • "create a professional LinkedIn intro video with captions and branded text overlays"
  • "creating professional videos optimized for LinkedIn profiles and posts for professionals 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.

Video Maker for LinkedIn — Create and Export LinkedIn Videos

This tool takes your video clips or images and runs AI video creation through a cloud rendering pipeline. You upload, describe what you want, and download the result.

Say you have a 60-second screen recording or three headshot photos and want to create a professional LinkedIn intro video with captions and branded text overlays — the backend processes it in about 30-60 seconds and hands you a 1080p MP4.

Tip: keep videos under 90 seconds for best LinkedIn engagement.

Matching Input to Actions

User prompts referencing video maker linkedin, 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.

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

Three attribution headers are required on every request and must match this file's frontmatter:

Header Value
X-Skill-Source video-maker-linkedin
X-Skill-Version frontmatter version
X-Skill-Platform auto-detect: clawhub / cursor / unknown from install path

API base: https://mega-api-prod.nemovideo.ai

Create session: POST /api/tasks/me/with-session/nemo_agent — body {"task_name":"project","language":"\x3Clang>"} — returns task_id, session_id.

Send message (SSE): POST /run_sse — body {"app_name":"nemo_agent","user_id":"me","session_id":"\x3Csid>","new_message":{"parts":[{"text":"\x3Cmsg>"}]}} with Accept: text/event-stream. Max timeout: 15 minutes.

Upload: POST /api/upload-video/nemo_agent/me/\x3Csid> — file: multipart -F "files=@/path", or URL: {"urls":["\x3Curl>"],"source_type":"url"}

Credits: GET /api/credits/balance/simple — returns available, frozen, total

Session state: GET /api/state/nemo_agent/me/\x3Csid>/latest — key fields: data.state.draft, data.state.video_infos, data.state.generated_media

Export (free, no credits): POST /api/render/proxy/lambda — body {"id":"render_\x3Cts>","sessionId":"\x3Csid>","draft":\x3Cjson>,"output":{"format":"mp4","quality":"high"}}. Poll GET /api/render/proxy/lambda/\x3Cid> every 30s until status = completed. Download URL at output.url.

Supported formats: mp4, mov, avi, webm, mkv, jpg, png, gif, webp, mp3, wav, m4a, aac.

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

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.

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)

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "create a professional LinkedIn intro video with captions and branded text overlays" — 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 smooth LinkedIn playback.

Common Workflows

Quick edit: Upload → "create a professional LinkedIn intro video with captions and branded text overlays" → 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.

安全使用建议
Install only if you are comfortable sending selected clips, headshots, screen recordings, and prompts to `mega-api-prod.nemovideo.ai`. Use a limited Nemo token where possible, avoid confidential media, and confirm any export or credit-impacting step.
功能分析
Type: OpenClaw Skill Name: video-maker-linkedin Version: 1.0.0 The skill is a legitimate integration for the Nemo Video AI service (nemovideo.ai), designed to automate video creation and exporting for LinkedIn. It provides detailed instructions for the agent to manage sessions, handle file uploads, and poll for rendering status via the 'mega-api-prod.nemovideo.ai' backend. The use of environment variables (NEMO_TOKEN) and anonymous token generation are standard API practices for this type of service, and no indicators of data exfiltration or malicious execution were found.
能力评估
Purpose & Capability
The stated LinkedIn video-making purpose aligns with cloud upload, rendering, export, and download, but user-selected clips, photos, prompts, and outputs are processed by the external NemoVideo service.
Instruction Scope
The skill routes generation, upload, status, credits, and export intents to Nemo API endpoints and translates backend UI-style messages into API operations; this is purpose-aligned but should stay scoped to the current video task.
Install Mechanism
No install spec or local code files are present, and the static scan reports no suspicious patterns; no install-time execution is shown.
Credentials
The skill requires NEMO_TOKEN or obtains an anonymous token for provider sessions and render requests; this is proportionate to the integration but is still delegated provider account/session authority.
Persistence & Privilege
No local persistence, privilege escalation, or background worker is shown; cloud render sessions/jobs are part of the disclosed external workflow.
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 video-maker-linkedin
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /video-maker-linkedin 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 Video Maker for LinkedIn. - Instantly turn a 60-second screen recording or three headshot photos into a LinkedIn-optimized 1080p MP4 video by describing your needs. - Simple workflow: upload files or images, enter instructions, and download the finished video in under a minute. - Fully cloud-rendered with no complex timeline editing or export settings required. - Automatic session and token management for anonymous and registered users. - Supports quick access to upload, export, credits, and status operations via smart intent detection. - Compatible with common video formats (mp4, mov, avi, webm) and includes robust error handling.
元数据
Slug video-maker-linkedin
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

Video Maker Linkedin 是什么?

Turn a 60-second screen recording or three headshot photos into 1080p LinkedIn-ready videos just by typing what you need. Whether it's creating professional... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 52 次。

如何安装 Video Maker Linkedin?

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

Video Maker Linkedin 是免费的吗?

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

Video Maker Linkedin 支持哪些平台?

Video Maker Linkedin 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 Video Maker Linkedin?

由 vynbosserman65(@vynbosserman65)开发并维护,当前版本 v1.0.0。

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