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Daily Review Editor Online

作者 mory128 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install daily-review-editor-online
功能描述
Turn a 3-minute daily vlog or review recording into 1080p polished review clips just by typing what you need. Whether it's editing and publishing daily revie...
使用说明 (SKILL.md)

Getting Started

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

Try saying:

  • "edit my daily review footage"
  • "export 1080p MP4"
  • "trim pauses, add section titles, and"

Quick Start Setup

This skill connects to a cloud processing backend. On first use, set up the connection automatically and let the user know ("Connecting...").

Token check: Look for NEMO_TOKEN in the environment. If found, skip to session creation. Otherwise:

  • Generate a UUID as client identifier
  • POST https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with X-Client-Id header
  • Extract data.token from the response — this is your NEMO_TOKEN (100 free credits, 7-day expiry)

Session: POST https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Keep the returned session_id for all operations.

Let the user know with a brief "Ready!" when setup is complete. Don't expose tokens or raw API output.

Daily Review Editor Online — Edit and Publish Review Videos

This tool takes your daily review footage and runs AI review editing through a cloud rendering pipeline. You upload, describe what you want, and download the result.

Say you have a 3-minute daily vlog or review recording and want to trim pauses, add section titles, and export a clean daily review video — the backend processes it in about 1-2 minutes and hands you a 1080p MP4.

Tip: keep your review under 5 minutes for fastest processing and cleaner AI cuts.

Matching Input to Actions

User prompts referencing daily review editor online, 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.

Skill attribution — read from this file's YAML frontmatter at runtime:

  • X-Skill-Source: daily-review-editor-online
  • 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.

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.

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

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)

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

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "trim pauses, add section titles, and export a clean daily review 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 YouTube, Instagram, and review platforms.

Common Workflows

Quick edit: Upload → "trim pauses, add section titles, and export a clean daily review 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 appears to be a cloud video-editing front end and mostly asks for the expected credential (NEMO_TOKEN). Before installing, consider: 1) Do you trust the external host (mega-api-prod.nemovideo.ai) to receive your raw video uploads? Uploaded videos may contain sensitive data. 2) The skill may inspect your home directory to detect install paths and may read ~/.config/nemovideo/ (the SKILL.md frontmatter mentions this) — if you keep tokens or other secrets there, confirm whether the skill will read or transmit them. 3) If you don't want the skill to mint or use an anonymous token automatically, provide a short-lived token or ask the author to make anonymous-token creation explicit and optional. 4) Ask the skill author/registry to fix the metadata mismatch (registry says no configPaths; SKILL.md lists ~/.config/nemovideo/) and to document whether any tokens are persisted locally. If you need lower risk, only use with ephemeral or limited-scope credentials and avoid uploading videos containing sensitive information.
功能分析
Type: OpenClaw Skill Name: daily-review-editor-online Version: 1.0.0 The skill is a legitimate integration for a cloud-based video editing service hosted at mega-api-prod.nemovideo.ai. It facilitates video processing tasks such as trimming, title addition, and rendering through standard API calls (POST/GET/SSE). The instructions include security-conscious directives for the agent, such as masking authentication tokens (NEMO_TOKEN) and handling session states appropriately. No evidence of data exfiltration, malicious execution, or deceptive prompt injection was found in SKILL.md or _meta.json.
能力评估
Purpose & Capability
Name/description align with a cloud video-editing service and the only required credential (NEMO_TOKEN) fits that purpose. However, the SKILL.md frontmatter lists a required config path (~/.config/nemovideo/) while the registry metadata shows no required config paths — this inconsistency should be resolved. Detecting an install path for attribution (reading ~/.clawhub/ or ~/.cursor/skills/) is plausible for telemetry/attribution but isn't clearly justified in the description.
Instruction Scope
Instructions ask the agent to: read NEMO_TOKEN from the environment (expected), generate an anonymous token via a network POST if none exists (creates/uses a server-issued token), read the skill's own YAML frontmatter for attribution, and detect install paths in the user's home directory. The upload and export flows require reading user files or URLs (expected for video upload). The main concerns: (1) the plan to examine install/config paths in the user's home directory is privacy-sensitive and not spelled out to the user; (2) the skill will call an external API to mint tokens automatically, which changes credential state even if no token was provided initially.
Install Mechanism
Instruction-only skill with no install spec and no code files — lowest install risk. No downloads or package installs are specified.
Credentials
Only NEMO_TOKEN is declared as required, which is appropriate for a cloud API. The SKILL.md additionally references a config path (~/.config/nemovideo/) in its frontmatter metadata (not declared in registry), implying the agent may read that directory for credentials/config — this expands scope beyond the single declared env var and should be justified. The anonymous-token flow mints a short-lived token if none exists; that behavior is plausible but notable because it causes outbound network auth activity without an explicit user-provided key.
Persistence & Privilege
The skill does not request always:true and does not claim to modify other skills or global agent settings. It creates session tokens on the backend and may leave orphaned jobs if a session is closed, which is a server-side persistence concern rather than elevated local 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 daily-review-editor-online
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /daily-review-editor-online 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 Daily Review Editor Online. - Upload daily review footage, describe edits, and export 1080p MP4s in 1-2 minutes—no desktop software needed. - Automatic cloud session setup with 100 free credits for new users. - Supports instant actions: editing, uploading, exporting, credits check, and video state review. - Clear troubleshooting and user prompts for smooth workflow and backend communication. - Full support for major file formats (video, audio, images); handles file size and subscription limitations gracefully.
元数据
Slug daily-review-editor-online
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

Daily Review Editor Online 是什么?

Turn a 3-minute daily vlog or review recording into 1080p polished review clips just by typing what you need. Whether it's editing and publishing daily revie... 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 Daily Review Editor Online?

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

Daily Review Editor Online 是免费的吗?

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

Daily Review Editor Online 支持哪些平台?

Daily Review Editor Online 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 Daily Review Editor Online?

由 mory128(@mory128)开发并维护,当前版本 v1.0.0。

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