← 返回 Skills 市场
francemichaell-15

Best Video Trimmer

作者 francemichaell-15 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
52
总下载
0
收藏
0
当前安装
1
版本数
在 OpenClaw 中安装
/install best-video-trimmer
功能描述
Get trimmed video clips ready to post, without touching a single slider. Upload your video clips (MP4, MOV, AVI, WebM, up to 500MB), say something like "trim...
使用说明 (SKILL.md)

Getting Started

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

Try saying:

  • "trim my video clips"
  • "export 1080p MP4"
  • "trim the first 30 seconds and"

Automatic Setup

On first interaction, connect to the processing API before doing anything else. Show a brief status like "Setting things up...".

Token: If NEMO_TOKEN environment variable is already set, use it and skip to Session below.

Free token: Generate a UUID as client identifier, then POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id: \x3Cuuid>. The response field data.token becomes your NEMO_TOKEN (100 credits, 7-day expiry).

Session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Save session_id from the response.

Confirm to the user you're connected and ready. Don't print tokens or raw JSON.

Best Video Trimmer — Trim and Export Clean Clips

Send me your video clips and describe the result you want. The AI video trimming runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload a 10-minute raw interview recording, type "trim the first 30 seconds and cut the pauses in the middle", and you'll get a 1080p MP4 back in roughly 20-40 seconds. All rendering happens server-side.

Worth noting: shorter source clips process faster and give more precise trim points.

Matching Input to Actions

User prompts referencing best video trimmer, 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 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.

Headers are derived from this file's YAML frontmatter. X-Skill-Source is best-video-trimmer, X-Skill-Version comes from the version field, and X-Skill-Platform is detected from the install path (~/.clawhub/ = clawhub, ~/.cursor/skills/ = cursor, otherwise 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 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

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

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 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)

Common Workflows

Quick edit: Upload → "trim the first 30 seconds and cut the pauses in the middle" → Download MP4. Takes 20-40 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 "trim the first 30 seconds and cut the pauses in the middle" — 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 platforms and devices.

安全使用建议
This skill appears to be what it says: a cloud-based video trimming service that uploads your media to nemo-video's API and requires a service token. Before installing or using it: (1) Understand that your videos will be transmitted to https://mega-api-prod.nemovideo.ai — do not upload private/sensitive footage unless you trust that operator. (2) The skill needs a NEMO_TOKEN; use the anonymous-token flow if you prefer temporary tokens rather than providing a long-lived credential. (3) The SKILL.md references storing session info and a local config path (~/.config/nemovideo/); verify where tokens/session IDs are stored and how long they persist on disk. (4) Confirm the privacy/retention policy of the remote service and whether uploaded media or derived assets are retained or used for training. (5) Note a small metadata inconsistency (registry shows no configPaths but the skill's internal metadata lists one) — ask the publisher to clarify what local files are read/written. If you need the skill to never send media off your machine, do not install/use it.
功能分析
Type: OpenClaw Skill Name: best-video-trimmer Version: 1.0.0 The skill bundle is a legitimate integration for a video trimming service hosted at nemovideo.ai. It provides detailed instructions for the agent to manage sessions, upload files, and trigger cloud-based video rendering via the mega-api-prod.nemovideo.ai endpoint. All network activity and file access (e.g., ~/.config/nemovideo/ and checking installation paths for platform attribution) are directly related to the service's stated functionality, with no evidence of data exfiltration, credential theft, or malicious intent.
能力评估
Purpose & Capability
The skill claims to perform cloud video trimming and its runtime instructions exclusively call a remote rendering API and require a single service token (NEMO_TOKEN). Requiring an API token and uploading videos to the service is coherent with the stated purpose.
Instruction Scope
The SKILL.md explicitly instructs the agent to upload user video files or URLs and to exchange/refresh tokens via the remote endpoints (anonymous-token, session creation, upload, render, etc.). This is expected for a cloud-rendering workflow, but it means user media and metadata will be sent off-host. The doc also describes deriving headers from local install path detection (to set X-Skill-Platform), and saving session_id — these imply accessing local environment/state for attribution and local storage of session data; that behavior is plausible but worth noting.
Install Mechanism
No install spec or code files are present (instruction-only). Nothing is written to disk or downloaded by an install step in the skill bundle itself, which reduces installation risk.
Credentials
Only a single credential (NEMO_TOKEN) is requested, which matches the described cloud API usage. However, the SKILL.md includes metadata that references a config path (~/.config/nemovideo/) not declared in the registry summary — that suggests the skill may read or write a local config directory to store tokens or session info; this is plausible for convenience but is not surfaced in the registry metadata and should be disclosed.
Persistence & Privilege
The skill is not configured as always:true and does not request elevated platform privileges. Autonomous invocation is allowed (the platform default) but there is no evidence this skill requests persistent, system-level presence or modifies 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 best-video-trimmer
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /best-video-trimmer 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 Best Video Trimmer — Trim and Export Clean Clips. - Upload videos (MP4, MOV, AVI, WebM up to 500MB) and describe edits in plain language. - Automatic connection to secure GPU cloud processing, with easy session and token setup. - Supports AI-powered trimming, pause removal, and batch or iterative editing workflows. - Export edited clips as 1080p MP4 and other formats in seconds. - Built-in credit management, full API error handling, and simple status updates throughout your workflow.
元数据
Slug best-video-trimmer
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

Best Video Trimmer 是什么?

Get trimmed video clips ready to post, without touching a single slider. Upload your video clips (MP4, MOV, AVI, WebM, up to 500MB), say something like "trim... 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 Best Video Trimmer?

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

Best Video Trimmer 是免费的吗?

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

Best Video Trimmer 支持哪些平台?

Best Video Trimmer 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 Best Video Trimmer?

由 francemichaell-15(@francemichaell-15)开发并维护,当前版本 v1.0.0。

💬 留言讨论