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vcarolxhberger

Free Text Editor

作者 vcarolxhberger · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install free-text-editor
功能描述
Turn a 2-minute talking head video into 1080p text-edited videos just by typing what you need. Whether it's editing videos by modifying the transcript text i...
使用说明 (SKILL.md)

Getting Started

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

Try saying:

  • "edit my video clips"
  • "export 1080p MP4"
  • "edit the video by removing filler"

First-Time Connection

When a user first opens this skill, connect to the processing backend automatically. Briefly let them know (e.g. "Setting up...").

Authentication: Check if NEMO_TOKEN is set in the environment. If it is, skip to step 2.

  1. Obtain a free token: Generate a random UUID as client identifier. POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id set to that UUID. The response data.token is your NEMO_TOKEN — 100 free credits, valid 7 days.
  2. Create a session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Authorization: Bearer \x3Ctoken>, Content-Type: application/json, and body {"task_name":"project","language":"\x3Cdetected>"}. Store the returned session_id for all subsequent requests.

Keep setup communication brief. Don't display raw API responses or token values to the user.

Free Text Editor — Edit Videos by Editing Text

Drop your video clips in the chat and tell me what you need. I'll handle the AI text editing on cloud GPUs — you don't need anything installed locally.

Here's a typical use: you send a a 2-minute talking head video, ask for edit the video by removing filler words and trimming pauses using text, and about 30-60 seconds later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.

One thing worth knowing — deleting a word in the transcript automatically removes that segment from the video.

Matching Input to Actions

User prompts referencing free text editor, 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.

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

Header Value
X-Skill-Source free-text-editor
X-Skill-Version frontmatter version
X-Skill-Platform auto-detect: clawhub / cursor / unknown from install path

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

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

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.

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 "edit the video by removing filler words and trimming pauses using text" — 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.

Common Workflows

Quick edit: Upload → "edit the video by removing filler words and trimming pauses using text" → 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
This skill appears to do what it says: it uploads user-supplied video files to nemovideo.ai, obtains or uses a NEMO_TOKEN, and returns rendered download URLs. Before installing: (1) confirm you are comfortable uploading videos to an external service (privacy/PII concern); (2) ask the publisher whether session tokens or the anonymous NEMO_TOKEN are stored persistently and where (the frontmatter mentions ~/.config/nemovideo/ but the registry metadata does not); (3) if you supply your own NEMO_TOKEN, treat it as sensitive (revoke it if needed); (4) verify the domain (mega-api-prod.nemovideo.ai) and review that service's privacy/terms; and (5) if you prefer, supply your own token instead of letting the skill auto-create one. If the publisher can clarify persistence behavior (in-memory only vs. on-disk) and the config-path mismatch, the remaining questions are minor.
功能分析
Type: OpenClaw Skill Name: free-text-editor Version: 1.0.0 The skill bundle provides a legitimate integration for an AI-powered video editing service hosted at mega-api-prod.nemovideo.ai. The SKILL.md file contains detailed instructions for the agent to manage authentication tokens, handle session states, and process video editing tasks via API calls. There is no evidence of data exfiltration, malicious execution, or harmful prompt injection; the requested environment variables and configuration paths are specific to the service's functionality.
能力评估
Purpose & Capability
The skill is a cloud video text-editor and it asks only for a single service token (NEMO_TOKEN) and to communicate with nemovideo.ai endpoints. That credential and the described API calls are coherent with the stated purpose (uploading videos, editing via transcript, exporting rendered files). No unrelated cloud providers or system binaries are requested.
Instruction Scope
Instructions limit activity to the nemo backend: obtaining/using a token, creating a session, uploading video files, SSE chat, polling render status, and returning download URLs. It does not instruct reading arbitrary host files or other environment variables. The only scope ambiguity: the frontmatter references a config path (~/.config/nemovideo/) and the doc says to "store the returned session_id" but does not state whether this storage is temporary (in-memory) or persistent (on disk).
Install Mechanism
No install steps or external downloads are required—this is an instruction-only skill. That minimizes on-disk modifications and is proportionate for this kind of integration.
Credentials
Declared primaryEnv is NEMO_TOKEN which is appropriate. The skill will also auto-acquire an anonymous token by POSTing to the service if NEMO_TOKEN is not set; this is consistent with the service's anonymous flow but means the skill can create credentials for short-lived usage without an explicit user-provided token. The frontmatter claims a config path (~/.config/nemovideo/) while the registry metadata indicated none — this mismatch is unexplained and could imply persistent storage that wasn't documented elsewhere.
Persistence & Privilege
always:false and normal autonomous invocation are fine. The only potential privilege/persistence issue is whether the skill writes session tokens or session_id to the user's config directory (~/.config/nemovideo/) or other persistent storage; the SKILL.md does not clearly specify where or whether data is persisted. If it does persist tokens locally, that increases the risk surface and you should know where/how it stores them and how to revoke them.
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 free-text-editor
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /free-text-editor 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 Free Text Editor. - Instantly edit talking head videos by modifying the transcript text instead of using a timeline. - Automatic backend setup and authentication with 100 free credits for new users. - Drop video files, make text-based edit requests, and receive a 1080p MP4 export in under a minute. - Supports features like filler word removal, trimming pauses, credits checking, batch uploads, and multiple output formats. - Error handling and feedback for uploads, status checks, and export jobs.
元数据
Slug free-text-editor
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

Free Text Editor 是什么?

Turn a 2-minute talking head video into 1080p text-edited videos just by typing what you need. Whether it's editing videos by modifying the transcript text i... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 63 次。

如何安装 Free Text Editor?

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

Free Text Editor 是免费的吗?

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

Free Text Editor 支持哪些平台?

Free Text Editor 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 Free Text Editor?

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

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