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mhogan2013-9

Ai Anonymous Token

by mhogan2013-9 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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Install in OpenClaw
/install ai-anonymous-token
Description
Turn a 2-minute interview footage with visible faces into 1080p anonymized video files just by typing what you need. Whether it's automatically blurring face...
README (SKILL.md)

Getting Started

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

Try saying:

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

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.

AI Anonymous Token — Anonymize Faces in Videos

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

Here's a typical use: you send a a 2-minute interview footage with visible faces, ask for blur all faces and remove identifying details automatically, 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 with fewer faces process significantly faster and more accurately.

Matching Input to Actions

User prompts referencing ai 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.

Headers are derived from this file's YAML frontmatter. X-Skill-Source is ai-anonymous-token, 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.

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)

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

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.

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 "blur all faces and remove identifying details automatically" — 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.

Common Workflows

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

Usage Guidance
This skill will upload whatever video files you drop into the chat to an external service (mega-api-prod.nemovideo.ai) for cloud GPU processing and requires an API token (NEMO_TOKEN). Before installing or using it: 1) Don't upload highly sensitive or regulated footage (PHI, private interviews) until you verify the service, its privacy policy, and retention practices. 2) Prefer supplying your own NEMO_TOKEN from a trusted account rather than letting the skill auto-generate an anonymous token, since the skill will create and use a token if none is present. 3) Note the metadata/instruction mismatch (declared required env var vs. auto-token flow and a config path listed in SKILL.md but not in the registry); ask the publisher to clarify intended behavior. 4) If you need stronger assurance, request the service's official domain, published documentation, or run network traffic inspection to confirm where files are sent before use.
Capability Analysis
Type: OpenClaw Skill Name: ai-anonymous-token Version: 1.0.0 The ai-anonymous-token skill is a legitimate integration for a cloud-based video anonymization service (nemovideo.ai). It provides clear instructions for the AI agent to manage authentication via an 'anonymous token' workflow, handle video uploads, and process editing tasks through a documented API. While it performs environment detection to identify the host platform (e.g., OpenClaw or Cursor) for attribution headers, it does not attempt to exfiltrate sensitive local data, execute unauthorized commands, or establish persistence. All network activity is directed to the stated service domain (mega-api-prod.nemovideo.ai) and is consistent with the skill's described purpose.
Capability Assessment
Purpose & Capability
The skill claims to anonymize videos using a cloud backend and all API endpoints and headers in SKILL.md align with that purpose. Requesting a NEMO_TOKEN as the primary credential is coherent. However, metadata in the SKILL.md also lists a config path (~/.config/nemovideo/) while the registry metadata reported no required config paths—this mismatch is inconsistent.
Instruction Scope
Runtime instructions direct the agent to accept user video files and upload them to https://mega-api-prod.nemovideo.ai, create sessions, poll renders, and include specific headers. They also instruct the agent to create an anonymous token by POSTing to the provider if NEMO_TOKEN is missing and to derive X-Skill-Platform from the agent's install path (which implies reading filesystem/installation context). Uploading user videos and automatically creating tokens are central to the feature but are sensitive actions; the instructions do not include safeguards beyond 'don't expose tokens' and they contradict the registry's claim that NEMO_TOKEN is required.
Install Mechanism
No install spec and no code files were provided (instruction-only). This minimizes local persistence and file writes; the skill operates purely via network calls described in SKILL.md.
Credentials
The skill only requests one credential (NEMO_TOKEN), which is appropriate for a cloud API. However, there's an inconsistency: the skill declares NEMO_TOKEN required, yet the instructions include an automatic anonymous-token creation flow when the env var is absent. The SKILL.md metadata also mentions a config path (~/ .config/nemovideo/) not reflected in the registry summary—this mismatch should be clarified.
Persistence & Privilege
always is false and there is no install or code writing to disk; the skill asks the agent to hold a temporary session token for job management. It does not request persistent system-wide privileges or modify other skills.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install ai-anonymous-token
  3. After installation, invoke the skill by name or use /ai-anonymous-token
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
AI Anonymous Token 1.0.0 — Initial Release - Instantly anonymize faces in up to 2-minute video clips with AI, no timeline editing required. - Fast cloud-based processing with simple upload, 1080p export, and quick download workflow. - Automatically creates or fetches authentication tokens (NEMO_TOKEN) for secure uploads and jobs. - Supports common video and audio formats (mp4, mov, avi, webm, mp3, wav, etc) up to 500MB. - User-friendly prompts: just describe your edits (“blur faces”, “remove identifying details”) and get results in 1–2 minutes. - Includes error handling for missing tokens, large files, and export limitations.
Metadata
Slug ai-anonymous-token
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Ai Anonymous Token?

Turn a 2-minute interview footage with visible faces into 1080p anonymized video files just by typing what you need. Whether it's automatically blurring face... It is an AI Agent Skill for Claude Code / OpenClaw, with 83 downloads so far.

How do I install Ai Anonymous Token?

Run "/install ai-anonymous-token" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Ai Anonymous Token free?

Yes, Ai Anonymous Token is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Ai Anonymous Token support?

Ai Anonymous Token is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Ai Anonymous Token?

It is built and maintained by mhogan2013-9 (@mhogan2013-9); the current version is v1.0.0.

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