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Ai Highlight Video Maker Free

作者 tk8544-b · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
102
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当前安装
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版本数
在 OpenClaw 中安装
/install ai-highlight-video-maker-free
功能描述
generate raw video footage into highlight reel clips with this skill. Works with MP4, MOV, AVI, WebM files up to 500MB. sports creators, TikTok creators, eve...
使用说明 (SKILL.md)

Getting Started

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

Try saying:

  • "generate my raw video footage"
  • "export 1080p MP4"
  • "extract the best moments and compile"

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.

AI Highlight Video Maker Free — Extract and Export Video Highlights

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

A quick example: upload a 2-hour sports game recording, type "extract the best moments and compile them into a 60-second highlight reel", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: shorter source videos under 10 minutes produce faster and more accurate highlights.

Matching Input to Actions

User prompts referencing ai highlight video maker free, 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.

Every API call needs Authorization: Bearer \x3CNEMO_TOKEN> plus the three attribution headers above. If any header is missing, exports return 402.

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

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

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

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.

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)

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "extract the best moments and compile them into a 60-second highlight reel" — 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 social platforms.

Common Workflows

Quick edit: Upload → "extract the best moments and compile them into a 60-second highlight reel" → 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 be a cloud-based video highlight exporter and will call https://mega-api-prod.nemovideo.ai to create sessions, upload video, and return download URLs. Two things to check before installing: (1) The registry lists NEMO_TOKEN as required, but the instructions say the agent will obtain an anonymous token if none is present — decide whether you want the agent using your personal NEMO_TOKEN (a bearer token sent to the remote API) or let it get a temporary anonymous token. (2) The skill's metadata mentions reading ~/.config/nemovideo/ and detecting install paths to set headers; that implies filesystem reads beyond only the skill file. If you have sensitive data in that directory, remove it or deny the skill access. Also verify you trust mega-api-prod.nemovideo.ai (privacy of uploads, retention, and billing), and prefer to test with non-sensitive clips or with the anonymous flow first. If you need higher assurance, ask the publisher for clarifications about what local files are read and whether NEMO_TOKEN is strictly required.
功能分析
Type: OpenClaw Skill Name: ai-highlight-video-maker-free Version: 1.0.0 The skill is a legitimate integration for the NemoVideo AI service, facilitating video highlight generation through a remote API (mega-api-prod.nemovideo.ai). It manages authentication, file uploads, and rendering tasks as described in SKILL.md. While it includes telemetry for platform attribution and requires access to specific environment variables (NEMO_TOKEN), its behavior is transparent and aligned with its stated purpose without evidence of malicious intent, unauthorized data exfiltration, or prompt injection attacks.
能力评估
Purpose & Capability
The skill's stated purpose (cloud-based highlight extraction) matches the API calls in SKILL.md and the need for a NEMO_TOKEN. However the registry declares NEMO_TOKEN as required while the runtime instructions explicitly support obtaining an anonymous token if NEMO_TOKEN is absent — that is an inconsistency. The declared config path (~/.config/nemovideo/) is plausible for a video tool but not justified in the prose.
Instruction Scope
Runtime instructions tell the agent to (a) use NEMO_TOKEN if present or else POST for an anonymous token, (b) create sessions, upload files, run SSE, and poll renders on https://mega-api-prod.nemovideo.ai — all consistent with a remote renderer. But the skill also instructs reading its own YAML frontmatter and detecting install path (~/.clawhub/, ~/.cursor/skills/) to set X-Skill-Platform, and metadata declares a config path (~/.config/nemovideo/). Those steps require file-system reads; the manifest doesn't clearly justify reading user config directories. The instructions also refer to 'three attribution headers above' but the doc is slightly sloppy about which exact headers are required.
Install Mechanism
Instruction-only skill with no install spec and no code files. This is low-risk from an install perspective — nothing will be dropped to disk by an installer step.
Credentials
Only one credential (NEMO_TOKEN) is declared, which is appropriate for a cloud API. However, declaring it as required while the SKILL.md supports anonymous-token acquisition is inconsistent. The declared config path could expose local tokens/config if the agent reads it; that access should be explicit and justified.
Persistence & Privilege
No always:true flag, no unusual persistence. Agent autonomy is allowed (platform default) but not itself an additional red flag 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-highlight-video-maker-free
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /ai-highlight-video-maker-free 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 Highlight Video Maker Free — Initial Release - Upload raw video footage (MP4, MOV, AVI, WebM up to 500MB) and generate highlight reels using AI in 1–2 minutes. - No installation required; all processing and rendering handled on remote GPU servers. - Simple onboarding: connects via NEMO_TOKEN or acquires free credits automatically. - Supports export to 1080p MP4 with fast, cloud-based workflow. - Includes session management, balance checks, and robust error handling. - Clean chat interface: keeps technical details hidden, offers clear status updates.
元数据
Slug ai-highlight-video-maker-free
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 Highlight Video Maker Free 是什么?

generate raw video footage into highlight reel clips with this skill. Works with MP4, MOV, AVI, WebM files up to 500MB. sports creators, TikTok creators, eve... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 102 次。

如何安装 Ai Highlight Video Maker Free?

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

Ai Highlight Video Maker Free 是免费的吗?

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

Ai Highlight Video Maker Free 支持哪些平台?

Ai Highlight Video Maker Free 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 Highlight Video Maker Free?

由 tk8544-b(@tk8544-b)开发并维护,当前版本 v1.0.0。

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