← 返回 Skills 市场
peand-rover

Editor Job

作者 peandrover adam · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
68
总下载
0
收藏
0
当前安装
1
版本数
在 OpenClaw 中安装
/install editor-job
功能描述
edit raw video footage into polished edited clips with this skill. Works with MP4, MOV, AVI, WebM files up to 500MB. freelance video editors use it for editi...
使用说明 (SKILL.md)

Getting Started

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

Try saying:

  • "edit my raw video footage"
  • "export 1080p MP4"
  • "cut the pauses, add transitions, 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.

Editor Job — Edit and Export Finished Videos

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

Here's a typical use: you send a a 3-minute unedited interview recording, ask for cut the pauses, add transitions, and export a clean final cut, and about 1-2 minutes later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.

One thing worth knowing — shorter clips under 2 minutes process significantly faster and give more precise AI cuts.

Matching Input to Actions

User prompts referencing editor job, 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.

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

Header Value
X-Skill-Source editor-job
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.

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.

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)

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

Common Workflows

Quick edit: Upload → "cut the pauses, add transitions, and export a clean final cut" → 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.

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "cut the pauses, add transitions, and export a clean final cut" — 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 clients.

安全使用建议
This skill appears to be a normal cloud video-editing integration, but double-check a few things before use: (1) Confirm the NEMO_TOKEN comes from a trusted source — it's a bearer token used on every request and grants access to your account/credits. (2) Prefer using the anonymous-token flow if you don't want to supply a personal account token. (3) Ask the publisher to clarify the frontmatter configPaths entry (~/.config/nemovideo/) and whether the agent will read that directory; avoid installing if the agent will read arbitrary local config files. (4) Don't upload sensitive or private footage until you verify the service's privacy/retention policy and the domain (mega-api-prod.nemovideo.ai). (5) Because metadata and frontmatter disagree, seek clarification from the skill author (unknown source) before granting credentials or uploading sensitive data.
功能分析
Type: OpenClaw Skill Name: editor-job Version: 1.0.0 The skill facilitates cloud video editing by uploading user files to a third-party API (mega-api-prod.nemovideo.ai) and automatically fetching credentials. It includes a high-risk 'GUI translation' mechanism in SKILL.md that instructs the agent to execute API actions based on instructions received from a backend SSE stream, which could be exploited for remote-triggered data exfiltration if the backend is compromised. Additionally, it performs environment probing by detecting the host platform from the installation path and requires access to local configuration paths.
能力评估
Purpose & Capability
Name and description (AI video editing) align with the actions described (upload, SSE-driven edits, render/export). The skill declares NEMO_TOKEN as its primary credential which fits a hosted editing service. However the SKILL.md frontmatter lists a config path (~/.config/nemovideo/) while the registry metadata earlier reported no required config paths — this inconsistency should be clarified.
Instruction Scope
Runtime instructions explicitly tell the agent to upload user video files and to call endpoints on mega-api-prod.nemovideo.ai (expected for this purpose). Concerns: the instructions also ask the agent to auto-detect 'platform' from the install path and reference a local config directory in frontmatter, which implies filesystem access beyond just reading a provided video. The document lacks explicit limits on what local files may be read and does not detail data-retention/privacy for uploads.
Install Mechanism
No install spec and no code files are present (instruction-only skill). This minimizes on-disk installation risk — nothing is downloaded or executed by an installer.
Credentials
Only a single credential (NEMO_TOKEN) is required which is proportional for a hosted API. The skill also documents a way to fetch an anonymous token via the API (no secret needed). The frontmatter's configPaths entry (~/ .config/nemovideo/) is the main proportionality concern: if the agent is permitted to read that path it could access persisted tokens or other local data — the skill does not justify that access in the runtime instructions.
Persistence & Privilege
always is false and the skill does not request to modify other skills or system-wide settings. It appears to operate per-session against the remote service and does not demand permanent platform-level 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 editor-job
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /editor-job 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 the Editor Job skill for AI-powered video editing and export. - Upload raw footage up to 500MB (MP4, MOV, AVI, WebM) and receive a polished 1080p MP4 in 1–2 minutes. - Handles edit commands like cutting pauses, adding transitions, and exporting final cuts. - Supports fast cloud processing with simple prompt-based workflows—no timeline work required. - Includes free token system for anonymous use, with credit and session management built-in. - Provides clear user feedback, error handling, and workflow tips for best results.
元数据
Slug editor-job
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 Job 是什么?

edit raw video footage into polished edited clips with this skill. Works with MP4, MOV, AVI, WebM files up to 500MB. freelance video editors use it for editi... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 68 次。

如何安装 Editor Job?

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

Editor Job 是免费的吗?

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

Editor Job 支持哪些平台?

Editor Job 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 Job?

由 peandrover adam(@peand-rover)开发并维护,当前版本 v1.0.0。

💬 留言讨论