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Easy Avatar Video

作者 mhogan2013-9 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install easy-avatar-video
功能描述
Cloud-based easy-avatar-video tool that handles creating spokesperson videos without filming real people. Upload TXT, DOCX, PDF, MP3 files (up to 200MB), des...
使用说明 (SKILL.md)

Getting Started

Share your text or script and I'll get started on AI avatar video creation. Or just tell me what you're thinking.

Try saying:

  • "generate my text or script"
  • "export 1080p MP4"
  • "create a talking avatar video from"

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.

Easy Avatar Video — Generate Avatar Presenter Videos Fast

Send me your text or script and describe the result you want. The AI avatar video creation runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload a 150-word product description script, type "create a talking avatar video from my script with a professional female presenter", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: shorter scripts under 2 minutes produce the most natural-looking avatar lip sync.

Matching Input to Actions

User prompts referencing easy avatar video, 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.

Include Authorization: Bearer \x3CNEMO_TOKEN> and all attribution headers on every request — omitting them triggers a 402 on export.

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

Header Value
X-Skill-Source easy-avatar-video
X-Skill-Version frontmatter version
X-Skill-Platform auto-detect: clawhub / cursor / unknown from install path

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.

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

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.

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 → "create a talking avatar video from my script with a professional female presenter" → 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 "create a talking avatar video from my script with a professional female presenter" — concrete instructions get better results.

Max file size is 200MB. Stick to TXT, DOCX, PDF, MP3 for the smoothest experience.

Export as MP4 for widest compatibility.

安全使用建议
This skill mostly does what it says (remote avatar video rendering) and only requests one API token, but there are a few red flags you should check before installing: (1) Verify the skill source and owner — no homepage or known publisher is provided. (2) Confirm the domain (mega-api-prod.nemovideo.ai) is legitimate for the service you intend to use. (3) Prefer using the anonymous-token flow for ephemeral tokens rather than placing a long-lived NEMO_TOKEN in your environment. (4) Inspect and confirm why ~/.config/nemovideo/ is needed (registry metadata vs frontmatter mismatch). Don't give broad or long-lived credentials unless you trust the service. (5) Review the SKILL.md for invisible/control characters (the scanner flagged unicode-control-chars). (6) Test with non-sensitive/dummy data first and monitor outbound requests and logs. If you are unsure about the token scope or where session tokens are stored, do not install or share real credentials until the developer clarifies these points.
功能分析
Type: OpenClaw Skill Name: easy-avatar-video Version: 1.0.0 The skill provides a legitimate integration for an AI avatar video generation service hosted at nemovideo.ai. It defines standard API workflows for session management, file uploads, and video rendering, including an anonymous authentication flow. No evidence of data exfiltration, malicious command execution, or harmful prompt injection was found in SKILL.md or _meta.json.
能力评估
Purpose & Capability
The name/description (avatar video generation) aligns with the runtime instructions which call a nemovideo.ai rendering API and accept uploads. The skill declares NEMO_TOKEN as the primary credential which is consistent with a cloud API. However, the SKILL.md frontmatter requests a config path (~/.config/nemovideo/) while the registry metadata at the top listed no required config paths — this mismatch is incoherent and should be clarified.
Instruction Scope
The SKILL.md gives detailed runtime steps: use NEMO_TOKEN if present, otherwise obtain an anonymous token via POST to https://mega-api-prod.nemovideo.ai, create sessions, post SSE messages, upload user files, and poll renders. Those actions match the stated purpose, but the file contains a detected prompt-injection pattern (unicode-control-chars). The instructions also require the agent to 'auto-detect' an install path for X-Skill-Platform and to include attribution headers that must match the frontmatter — these add extra system probing (reading install path/frontmatter) and risk accidental leakage. The doc explicitly tells the agent not to print tokens, but it does not specify secure storage for tokens/session IDs.
Install Mechanism
Instruction-only skill with no install spec and no code files; nothing will be written to disk by an installer. This is the lowest install risk.
Credentials
Only one required environment variable (NEMO_TOKEN) is declared, which is proportionate to a cloud API integration. However, there is an inconsistency: the registry summary says no required config paths, while the SKILL.md frontmatter lists ~/.config/nemovideo/ as a required config path. That suggests the skill may expect to read files from that directory (credentials/config) which increases sensitivity. The anonymous-token flow is provided as a fallback, which is preferable to requiring a long-lived token, but the skill does not explain secure handling of tokens.
Persistence & Privilege
The skill is not forced-always and does not declare system-wide persistence. It asks to persist a session_id (typical for remote APIs), but it does not ask to modify other skills or system settings. Default autonomous invocation is allowed (normal), so if you enable the skill it could be invoked without explicit user action — combine that fact with credential use if you are concerned.
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 easy-avatar-video
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /easy-avatar-video 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
easy-avatar-video 1.0.0 — Initial Release - Generate AI avatar presenter videos in the cloud from text, scripts, or audio uploads. - Supports quick uploads of TXT, DOCX, PDF, MP3 files (up to 200MB). - Outputs 1080p MP4 videos in about 1–2 minutes; all processing is server-side. - Built-in handling for setup, session, uploads, export, credits, and state management. - No filming required; ideal for marketers creating spokesperson videos from scripts. - User-friendly workflows for creating, previewing, and exporting avatar videos.
元数据
Slug easy-avatar-video
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

Easy Avatar Video 是什么?

Cloud-based easy-avatar-video tool that handles creating spokesperson videos without filming real people. Upload TXT, DOCX, PDF, MP3 files (up to 200MB), des... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 94 次。

如何安装 Easy Avatar Video?

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

Easy Avatar Video 是免费的吗?

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

Easy Avatar Video 支持哪些平台?

Easy Avatar Video 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 Easy Avatar Video?

由 mhogan2013-9(@mhogan2013-9)开发并维护,当前版本 v1.0.0。

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