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Ai Video Editor Maker Free

作者 vynbosserman65 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install ai-video-editor-maker-free
功能描述
edit raw video clips into polished edited videos with this skill. Works with MP4, MOV, AVI, WebM files up to 500MB. content creators and social media users u...
使用说明 (SKILL.md)

Getting Started

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

Try saying:

  • "edit my raw video clips"
  • "export 1080p MP4"
  • "trim the pauses, add transitions, and"

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 Video Editor Maker Free — Edit and Export Videos Free

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

A quick example: upload a 2-minute unedited screen recording, type "trim the pauses, add transitions, and export a clean final video", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: shorter clips under 60 seconds process significantly faster.

Matching Input to Actions

User prompts referencing ai video editor 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-video-editor-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

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 "trim the pauses, add transitions, and export a clean final video" — 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.

Common Workflows

Quick edit: Upload → "trim the pauses, add transitions, and export a clean final 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 behaves like a cloud video editor: it will upload your raw videos to a remote API (https://mega-api-prod.nemovideo.ai) and use a NEMO_TOKEN (or obtain a short-lived anonymous token) to process them. Before installing or invoking it: 1) Be aware that uploading sensitive or private footage will send it to a third party. 2) Confirm where your NEMO_TOKEN comes from and prefer scoped/minimal tokens; an anonymous token will be created automatically if none is present. 3) Note the SKILL.md asks the agent to probe install paths (~/.clawhub, ~/.cursor/skills) and references a config directory (~/.config/nemovideo/) — this is inconsistent with the registry metadata and could require filesystem reads; only allow such access if you trust the skill/source. 4) The skill has no homepage and an unknown owner; consider this lower provenance and exercise caution. If you need to proceed, restrict the token's permissions, avoid uploading sensitive content, and monitor network activity or run the skill in a sandboxed environment. Additional info (repo, privacy policy, or origin) would increase confidence.
功能分析
Type: OpenClaw Skill Name: ai-video-editor-maker-free Version: 1.0.0 The skill provides a functional interface for a cloud-based video editing service (nemovideo.ai). It manages authentication via the NEMO_TOKEN environment variable or an anonymous token exchange, handles file uploads, and processes video rendering through a defined API. No evidence of data exfiltration, unauthorized system access, or malicious prompt injection was found; the behavior is consistent with the stated purpose of the tool.
能力评估
Purpose & Capability
The skill claims to be a cloud video editor and only requires a NEMO_TOKEN — that is internally coherent. However the SKILL.md frontmatter advertises a config path (~/.config/nemovideo/) and runtime instructions ask the agent to detect install paths (~/.clawhub/, ~/.cursor/skills/) for header attribution. The registry metadata provided to the evaluator listed no required config paths, creating an inconsistency about what filesystem access the skill expects.
Instruction Scope
Instructions send user video files and metadata to https://mega-api-prod.nemovideo.ai (expected for a cloud editor) and describe SSE, uploads, exports, and token refresh flows. Concerningly, the runtime instructions also tell the agent to detect local install directories and read the skill's YAML frontmatter for attribution — this requires probing the user's home directories and reading filesystem paths outside the immediate request context. The skill will also, by design, upload raw user video content to a third-party server (privacy/data-exfiltration risk inherent to cloud editors).
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
Only a single credential is declared (NEMO_TOKEN), which is reasonable for an API-backed editor. However the SKILL.md frontmatter references a config path (~/.config/nemovideo/) and the agent is asked to probe install paths to set X-Skill-Platform — both imply filesystem access beyond just reading an env var. The metadata seen by the registry did not list those configPaths, so it's unclear whether the skill actually needs to read local config files that could contain other secrets.
Persistence & Privilege
always is false, autonomous invocation is allowed (platform default). The skill does not request permanent presence or claim to modify other skills or global agent settings.
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-video-editor-maker-free
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /ai-video-editor-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 Video Editor Maker Free — 1.0.0 - Initial release of AI-powered video editor that works with MP4, MOV, AVI, and WebM files up to 500MB. - Enables automated video editing and cloud export to 1080p MP4; no installation needed. - Supports uploading, timeline edits (trims, transitions, overlays, audio tracks), and fast cloud rendering. - Free to use with anonymous token and 100 free editing credits. - Delivers concise status updates and progress feedback during editing and export.
元数据
Slug ai-video-editor-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 Video Editor Maker Free 是什么?

edit raw video clips into polished edited videos with this skill. Works with MP4, MOV, AVI, WebM files up to 500MB. content creators and social media users u... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 67 次。

如何安装 Ai Video Editor Maker Free?

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

Ai Video Editor Maker Free 是免费的吗?

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

Ai Video Editor Maker Free 支持哪些平台?

Ai Video Editor 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 Video Editor Maker Free?

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

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