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susan4731-wilfordf

Audio Tts

作者 susan4731-wilfordf · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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当前安装
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在 OpenClaw 中安装
/install audio-tts
功能描述
convert text or script into voiced video clips with this skill. Works with TXT, DOCX, PDF, SRT files up to 200MB. content creators, marketers, educators use...
使用说明 (SKILL.md)

Getting Started

Got text or script to work with? Send it over and tell me what you need — I'll take care of the text to speech conversion.

Try saying:

  • "convert a 200-word product description script into a 1080p MP4"
  • "convert this script to a natural voiceover in English with a female voice"
  • "generating AI voiceovers from written scripts for content creators, marketers, educators"

First-Time Connection

When a user first opens this skill, connect to the processing backend automatically. Briefly let them know (e.g. "Setting up...").

Authentication: Check if NEMO_TOKEN is set in the environment. If it is, skip to step 2.

  1. Obtain a free token: Generate a random UUID as client identifier. POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id set to that UUID. The response data.token is your NEMO_TOKEN — 100 free credits, valid 7 days.
  2. Create a session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Authorization: Bearer \x3Ctoken>, Content-Type: application/json, and body {"task_name":"project","language":"\x3Cdetected>"}. Store the returned session_id for all subsequent requests.

Keep setup communication brief. Don't display raw API responses or token values to the user.

Audio TTS — Convert Text to Voiceover Video

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

A quick example: upload a 200-word product description script, type "convert this script to a natural voiceover in English with a female voice", and you'll get a 1080p MP4 back in roughly 20-40 seconds. All rendering happens server-side.

Worth noting: shorter text segments produce more natural-sounding speech output.

Matching Input to Actions

User prompts referencing audio tts, 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.

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

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

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 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

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "convert this script to a natural voiceover in English with a female voice" — concrete instructions get better results.

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

Export as MP4 for widest compatibility with video platforms.

Common Workflows

Quick edit: Upload → "convert this script to a natural voiceover in English with a female voice" → Download MP4. Takes 20-40 seconds 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 do what it claims (remote text→voiceover rendering) and asks only for a service token, but there are a few red flags to consider before installing: 1) Metadata mismatch — the SKILL.md references a local config path (~/.config/nemovideo/) that the registry metadata does not list; ask the publisher why the skill might read that folder. 2) Token/session persistence — the skill will generate an anonymous token and instruct you to "store" a session_id but doesn't say where; confirm whether tokens or session IDs will be saved to disk or only kept in-memory. 3) Privacy and retention — uploads and renders go to mega-api-prod.nemovideo.ai; request the service's privacy policy and data retention rules (do they keep uploaded scripts or generated media?). 4) Source and provenance — there is no homepage or source repo; prefer skills with a documented homepage or published client library you can audit. If you proceed, avoid supplying unrelated secrets (AWS keys, GitHub tokens, etc.), and restrict filesystem access if your agent platform allows it. Asking the publisher for a homepage, code examples showing how/where tokens are stored, and a privacy/retention statement would reduce risk.
功能分析
Type: OpenClaw Skill Name: audio-tts Version: 1.0.0 The skill 'audio-tts' facilitates text-to-video conversion via a remote API (nemovideo.ai), but contains instructions in SKILL.md that create a significant security risk. Specifically, it directs the agent to process a Server-Sent Events (SSE) stream from 'https://mega-api-prod.nemovideo.ai/run_sse' and execute 'tool calls' received from the backend. This effectively grants the remote server the ability to trigger any tools available to the agent (such as shell or filesystem access), which constitutes a remote control/execution vulnerability. Furthermore, it requires the agent to perform environment reconnaissance to determine its installation path for attribution headers and requests access to the user's home directory (~/.config/nemovideo/).
能力评估
Purpose & Capability
The skill claims to convert text into voiceover videos and only requests a single service credential (NEMO_TOKEN), which is coherent. However the SKILL.md frontmatter references a config path (~/.config/nemovideo/) while the registry metadata lists no required config paths — that mismatch is unexplained.
Instruction Scope
Runtime instructions call only the external nemo API endpoints needed for uploads, SSE, session creation, and exports (consistent with the stated purpose). The instructions also direct the agent to acquire an anonymous token if none is provided and to "store" the session_id for later calls — but they do not specify where/how to persist session/token data (in-memory vs disk vs agent config), which is ambiguous and worth clarifying.
Install Mechanism
This is an instruction-only skill with no install spec or code files, so nothing is written to disk by an installer. That is the lowest-risk install posture.
Credentials
The only declared required environment variable is NEMO_TOKEN, which is appropriate for a third-party TTS/rendering service. But the SKILL.md also lists a config path (~/.config/nemovideo/) in its frontmatter and requires auto-detection of the install path for X-Skill-Platform headers — both imply potential filesystem reads not declared in the registry metadata. This discrepancy makes it unclear what local data the skill will access.
Persistence & Privilege
always:false (good). The skill instructs the agent to create anonymous tokens and keep sessions alive across requests; it does not explicitly say it will modify other skills or system-wide settings. Clarify whether tokens/sessions are persisted to disk or saved only in-memory by the agent.
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 audio-tts
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /audio-tts 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
Audio TTS 1.0.0 — Initial Release - Convert text, DOCX, PDF, or SRT files (up to 200MB) into AI voiceover videos in 1080p MP4 format. - Automatic cloud processing with easy user authentication and session management. - Supports multiple workflows: single uploads, batch processing, and iterative editing. - Exposes clear status, export, balance, and upload actions mapped to user requests. - Returns results quickly (typically 20–40 seconds per job); full support for common video/audio formats. - Built-in guidance for file types, troubleshooting, and usage tips.
元数据
Slug audio-tts
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

Audio Tts 是什么?

convert text or script into voiced video clips with this skill. Works with TXT, DOCX, PDF, SRT files up to 200MB. content creators, marketers, educators use... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 65 次。

如何安装 Audio Tts?

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

Audio Tts 是免费的吗?

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

Audio Tts 支持哪些平台?

Audio Tts 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 Audio Tts?

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

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