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Ai Video Editor Descript

作者 mhogan2013-9 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install ai-video-editor-descript
功能描述
Get transcript-edited videos ready to post, without touching a single slider. Upload your raw video footage (MP4, MOV, AVI, WebM, up to 500MB), say something...
使用说明 (SKILL.md)

Getting Started

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

Try saying:

  • "edit my raw video footage"
  • "export 1080p MP4"
  • "remove filler words, add captions, 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.

AI Video Editor Descript — Edit Video by Editing Text

This tool takes your raw video footage and runs AI transcript-based editing through a cloud rendering pipeline. You upload, describe what you want, and download the result.

Say you have a 10-minute interview recording in MP4 and want to remove filler words, add captions, and trim silences automatically — the backend processes it in about 1-2 minutes and hands you a 1080p MP4.

Tip: shorter segments under 5 minutes process significantly faster and more accurately.

Matching Input to Actions

User prompts referencing ai video editor descript, 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: ai-video-editor-descript
  • X-Skill-Version: from frontmatter version
  • X-Skill-Platform: detect from install path (~/.clawhub/clawhub, ~/.cursor/skills/cursor, else unknown)

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

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

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.

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

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "remove filler words, add captions, and trim silences automatically" — 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 widest compatibility across platforms.

Common Workflows

Quick edit: Upload → "remove filler words, add captions, and trim silences automatically" → 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 normal cloud video-editing integration: it will use a NEMO_TOKEN to call nemovideo.ai, upload your media, start render jobs, and return download links. Before installing, confirm you trust the domain (mega-api-prod.nemovideo.ai) and are comfortable uploading the videos (they will be sent off-device). Note the minor inconsistencies: the skill frontmatter mentions a config path (~/.config/nemovideo/) and asks the agent to detect its install path to set attribution headers — this means the skill may read limited filesystem info for attribution. If you prefer, set NEMO_TOKEN yourself (rather than allowing anonymous token creation) and avoid uploading sensitive content until you verify the provider's privacy/retention policy. If you want higher assurance, ask the publisher for an official homepage or privacy docs and clarification about the configPath usage.
功能分析
Type: OpenClaw Skill Name: ai-video-editor-descript Version: 1.0.0 The skill is a legitimate integration for an AI video editing service (nemovideo.ai). It provides detailed instructions for the agent to manage authentication tokens, handle multipart file uploads, and process video editing tasks via Server-Sent Events (SSE). While it includes telemetry logic to detect the host platform (e.g., checking for ~/.clawhub/ or ~/.cursor/ paths), this is used for attribution headers (X-Skill-Platform) and the instructions explicitly advise the agent against leaking sensitive tokens or raw JSON to the user.
能力评估
Purpose & Capability
The skill is a cloud video-editing frontend and only requires a single API credential (NEMO_TOKEN) to call the described nemovideo.ai endpoints — this is proportional to the claimed functionality. Minor mismatch: the SKILL.md frontmatter lists a config path (~/.config/nemovideo/) whereas the registry metadata earlier reported no required config paths.
Instruction Scope
Runtime instructions confine actions to connecting to the nemovideo.ai API, uploading user-provided media, starting sessions, polling for render status, and returning download URLs. The skill asks the agent to detect install path (to set X-Skill-Platform) and to read the skill file frontmatter for version — these require limited filesystem/read access and are explainable for attribution headers, but they are broader than a purely stateless API client.
Install Mechanism
There is no install specification or third-party download; the skill is instruction-only so nothing is written to disk by an installer. This minimizes install-time risk.
Credentials
Only NEMO_TOKEN is declared as required and is appropriate for an API-backed service. The frontmatter also references a config path (~/.config/nemovideo/) that could be used to persist tokens/session info — the registry-level metadata did not list that, so there is an inconsistency to verify. No other credentials or secrets are requested.
Persistence & Privilege
Skill does not request always:true and does not ask to modify other skills or system-wide settings. It does instruct saving a session_id for ongoing operations (expected for a remote session workflow) but does not demand permanent elevated privileges.
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-descript
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /ai-video-editor-descript 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 AI Video Editor Descript (version 1.0.0). - Upload raw video footage (MP4, MOV, AVI, WebM, up to 500MB) and edit by describing changes in plain language. - Automatic transcript-based editing: remove filler words, add captions, trim silences, and more. - Simple, session-based workflow with free token generation and cloud processing. - Supports export to 1080p MP4 and other major formats; optimized for podcasters and fast-paced content creators. - Includes error handling, session management, and workflow tips for efficient AI-powered editing.
元数据
Slug ai-video-editor-descript
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 Descript 是什么?

Get transcript-edited videos ready to post, without touching a single slider. Upload your raw video footage (MP4, MOV, AVI, WebM, up to 500MB), say something... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 87 次。

如何安装 Ai Video Editor Descript?

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

Ai Video Editor Descript 是免费的吗?

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

Ai Video Editor Descript 支持哪些平台?

Ai Video Editor Descript 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 Descript?

由 mhogan2013-9(@mhogan2013-9)开发并维护,当前版本 v1.0.0。

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