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francemichaell-15

Editor List

作者 francemichaell-15 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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当前安装
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在 OpenClaw 中安装
/install editor-list
功能描述
Get editor access list ready to post, without touching a single slider. Upload your video clips (MP4, MOV, AVI, WebM, up to 500MB), say something like "show...
使用说明 (SKILL.md)

Getting Started

Got video clips to work with? Send it over and tell me what you need — I'll take care of the AI editor management.

Try saying:

  • "manage a 2-minute project with three collaborator editors assigned into a 1080p MP4"
  • "show me all editors on this project and their access levels"
  • "viewing and managing who has editor access to a video project for team leads, content managers, marketers"

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.

Editor List — Manage and View Project Editors

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

Here's a typical use: you send a a 2-minute project with three collaborator editors assigned, ask for show me all editors on this project and their access levels, and about under 10 seconds later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.

One thing worth knowing — removing an editor from the list does not delete their previous changes to the project.

Matching Input to Actions

User prompts referencing editor list, 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.

Base URL: https://mega-api-prod.nemovideo.ai

Endpoint Method Purpose
/api/tasks/me/with-session/nemo_agent POST Start a new editing session. Body: {"task_name":"project","language":"\x3Clang>"}. Returns session_id.
/run_sse POST Send a user message. Body includes app_name, session_id, new_message. Stream response with Accept: text/event-stream. Timeout: 15 min.
/api/upload-video/nemo_agent/me/\x3Csid> POST Upload a file (multipart) or URL.
/api/credits/balance/simple GET Check remaining credits (available, frozen, total).
/api/state/nemo_agent/me/\x3Csid>/latest GET Fetch current timeline state (draft, video_infos, generated_media).
/api/render/proxy/lambda POST Start export. Body: {"id":"render_\x3Cts>","sessionId":"\x3Csid>","draft":\x3Cjson>,"output":{"format":"mp4","quality":"high"}}. Poll status every 30s.

Accepted file types: mp4, mov, avi, webm, mkv, jpg, png, gif, webp, mp3, wav, m4a, aac.

Headers are derived from this file's YAML frontmatter. X-Skill-Source is editor-list, 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).

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.

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

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.

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

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 → "show me all editors on this project and their access levels" → Download MP4. Takes under 10 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 "show me all editors on this project and their access levels" — 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.

安全使用建议
This skill will upload whatever video files you provide to an external service at mega-api-prod.nemovideo.ai and will generate or use NEMO_TOKEN credentials (it may create an anonymous token if you don't supply one). Before installing or using it: 1) Consider privacy — your media and project data will leave your device and be processed on cloud GPUs; ask the publisher for a privacy/data-retention policy. 2) Note the skill has no homepage or publisher info in the registry — verify the service identity before trusting it with sensitive content. 3) The SKILL.md has an inconsistent config-path declaration (where it stores tokens/session is unclear) — ask how and where tokens/sessions are persisted and how to revoke them. 4) If you prefer control, set your own NEMO_TOKEN (from an account you trust) rather than allowing the skill to create anonymous credentials. 5) If you need higher assurance, request the skill author/publisher details or prefer a skill with a verifiable homepage and known owner.
功能分析
Type: OpenClaw Skill Name: editor-list Version: 1.0.0 The skill 'editor-list' exhibits a significant discrepancy between its stated purpose (managing project editor lists) and its actual implementation, which is a full-featured video editing and cloud rendering tool. The instructions in SKILL.md direct the agent to upload user video clips to a third-party backend (mega-api-prod.nemovideo.ai) and perform GPU-accelerated rendering, which is not transparently aligned with the 'Editor List' branding. Additionally, the _meta.json contains a future-dated publication timestamp (2026), and the skill automatically generates anonymous tokens and sessions, which could lead to unexpected data processing or credit consumption without clear user intent.
能力评估
Purpose & Capability
The skill's name/description (video editor access management and cloud render) aligns with requiring a NEMO_TOKEN and calling a remote render API. However, the SKILL.md frontmatter declares a config path (~/.config/nemovideo/) while the registry metadata said 'Required config paths: none' — this inconsistency about where credentials/session state are stored is unexplained. Also there is no homepage or publisher info to verify the service.
Instruction Scope
The instructions tell the agent to: check for NEMO_TOKEN, auto-generate an anonymous token by POSTing to https://mega-api-prod.nemovideo.ai, create sessions, and upload user video files (multipart) to that API. That means user media and session tokens will be sent to an external service — which is coherent with the stated purpose but is a privacy-sensitive action that the docs do not explicitly surface to end users. The SKILL.md also instructs to 'store the returned session_id for all subsequent requests' but does not specify where or how to persist it, creating ambiguity. It requires special attribution headers derived from install path detection; if the install path is unknown this may cause failures.
Install Mechanism
There is no install spec and no code files; this is instruction-only. That minimizes on-disk install risk.
Credentials
The only required environment variable is NEMO_TOKEN (declared as primary), which is appropriate for a remote video service. The skill also supports generating an anonymous token when none is present, which is plausible. The earlier-noted mismatch about configPaths (frontmatter vs registry) leaves unclear where tokens/session state will be written, and the skill will need permission to read attachments and upload them — reasonable for the feature but privacy-sensitive.
Persistence & Privilege
always is false and model invocation is allowed (normal). The skill's instructions imply storing session tokens and job IDs, but they do not request elevated privileges or modifications to other skills or system-wide settings. The persistence behavior is plausible but underspecified.
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 editor-list
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /editor-list 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
editor-list 1.0.0 - Initial release of a cloud-based tool for managing and viewing editor access in video projects. - Upload video clips (MP4, MOV, AVI, WebM up to 500MB), view and manage editor lists and their access levels, and export projects as 1080p MP4 files. - Automatic session and authentication handling using API tokens; requires no local installation. - Supports team workflows—assign/edit/remove collaborators and quickly review project editor status. - Key features include streamlined exports, clear error messaging, and session state management for fast project iteration.
元数据
Slug editor-list
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

Editor List 是什么?

Get editor access list ready to post, without touching a single slider. Upload your video clips (MP4, MOV, AVI, WebM, up to 500MB), say something like "show... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 82 次。

如何安装 Editor List?

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

Editor List 是免费的吗?

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

Editor List 支持哪些平台?

Editor List 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 Editor List?

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

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