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Best Anonymous Token

作者 susan4731-wilfordf · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install best-anonymous-token
功能描述
Skip the learning curve of professional editing software. Describe what you want — blur all faces and remove identifying details from this video — and get an...
使用说明 (SKILL.md)

Getting Started

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

Try saying:

  • "anonymize my video clips"
  • "export 1080p MP4"
  • "blur all faces and remove identifying"

Getting Connected

Before handling any user request, establish a connection to the backend API. Show a brief status like "Connecting...".

If NEMO_TOKEN is in the environment, use it directly and create a session. Otherwise, acquire a free starter token:

  • Generate a UUID as client identifier
  • POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with the X-Client-Id header
  • The response includes a token with 100 free credits valid for 7 days — use it as NEMO_TOKEN

Then create a session by POSTing to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer authorization and body {"task_name":"project","language":"en"}. The session_id in the response is needed for all following requests.

Tell the user you're ready. Keep the technical details out of the chat.

Best Anonymous Token — Anonymize and Export Protected Videos

Send me your video clips and describe the result you want. The AI identity anonymization runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload a 2-minute interview footage with visible faces, type "blur all faces and remove identifying details from this video", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: shorter clips with fewer faces process significantly faster and more accurately.

Matching Input to Actions

User prompts referencing best anonymous token, 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: best-anonymous-token
  • X-Skill-Version: from frontmatter version
  • X-Skill-Platform: detect from install path (~/.clawhub/clawhub, ~/.cursor/skills/cursor, else unknown)

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

Common Workflows

Quick edit: Upload → "blur all faces and remove identifying details from this 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.

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "blur all faces and remove identifying details from this 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 platforms and devices.

安全使用建议
This skill will upload your video files to https://mega-api-prod.nemovideo.ai for server-side anonymization and requires a NEMO_TOKEN. If you don't provide one, the skill will automatically request an anonymous token (by POSTing a generated UUID to the service). The SKILL.md also instructs detecting your agent's install path and references a local config directory (~/.config/nemovideo/), which implies the agent may probe local paths to set attribution headers. Before installing: (1) confirm the nemovideo.ai domain and service are legitimate and review their privacy policy; (2) avoid uploading sensitive or unredacted footage until you trust the service; (3) consider supplying your own NEMO_TOKEN rather than letting the skill auto-create one; (4) ask the skill author to explain the registry/frontmatter mismatch and why filesystem checks for install path are needed; (5) if you are uncomfortable with the agent probing local paths or automatic token creation, do not install.
功能分析
Type: OpenClaw Skill Name: best-anonymous-token Version: 1.0.0 The skill provides a functional interface for a video anonymization service hosted at mega-api-prod.nemovideo.ai. It manages authentication via the NEMO_TOKEN environment variable or an anonymous token acquisition flow and defines clear API interactions for uploading media, processing via SSE, and exporting rendered videos. The instructions in SKILL.md are consistent with the stated purpose of video editing and do not contain evidence of malicious intent, unauthorized data access, or harmful prompt injection.
能力评估
Purpose & Capability
The skill's name and description (anonymize/export videos) align with the API calls and workflows in SKILL.md (upload, render, export). Requesting a service token (NEMO_TOKEN) and calling nemovideo.ai endpoints is coherent with the stated purpose. However, the SKILL.md frontmatter mentions a required config path (~/.config/nemovideo/) and install-path-based attribution detection that are not reflected in the registry metadata — an inconsistency worth flagging.
Instruction Scope
Instructions direct the agent to: use NEMO_TOKEN if present; otherwise generate a UUID and POST to an anonymous-token endpoint to acquire a token; create sessions; upload user video files; poll render state; and always attach attribution headers. The upload/poll/export behavior is expected. The skill also instructs detecting the agent's install path (e.g., checking ~/.clawhub/ or ~/.cursor/skills/) to populate X-Skill-Platform, which implies probing the filesystem for install paths — this is outside pure video-processing logic and could read local paths/configs. Automatic token acquisition (silent generation of an anonymous token) is also a behavioral decision the user should be aware of.
Install Mechanism
This is an instruction-only skill with no install spec and no code files, so nothing is written to disk at install time. That minimizes install-time risk.
Credentials
The skill requires a single credential, NEMO_TOKEN, which is proportionate for calling the service. Two concerns: (1) the frontmatter in SKILL.md references a config path (~/.config/nemovideo/) even though the registry metadata lists no required config paths — a mismatch; (2) the skill will obtain an anonymous token automatically if none is present by posting to the remote auth endpoint. Automatic creation and use of credentials and the implied filesystem probing for attribution headers increase the scope of access and should be considered before granting permissions.
Persistence & Privilege
The skill is not marked always:true and does not request unusual persistent privileges. It is user-invocable and allows model invocation (normal for skills).
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 best-anonymous-token
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /best-anonymous-token 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 Best Anonymous Token — fast, AI-powered video anonymization for privacy protection. - Upload video files (MP4, MOV, AVI, WebM up to 500MB) for instant face blurring and identity removal. - No setup needed: session and token acquired automatically if not provided. - Cloud-based GPU processing, returning anonymized videos in 1–2 minutes. - Simple prompts control export, credit checking, status, and editing. - Supports batch and iterative workflows for journalists, researchers, and content creators.
元数据
Slug best-anonymous-token
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

Best Anonymous Token 是什么?

Skip the learning curve of professional editing software. Describe what you want — blur all faces and remove identifying details from this video — and get an... 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 Best Anonymous Token?

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

Best Anonymous Token 是免费的吗?

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

Best Anonymous Token 支持哪些平台?

Best Anonymous Token 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 Best Anonymous Token?

由 susan4731-wilfordf(@susan4731-wilfordf)开发并维护,当前版本 v1.0.0。

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