Skills ai-voice-over-generator

install
source · Clone the upstream repo
git clone https://github.com/openclaw/skills
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/openclaw/skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/bwbernardweston18/ai-voice-over-generator" ~/.claude/skills/clawdbot-skills-ai-voice-over-generator && rm -rf "$T"
manifest: skills/bwbernardweston18/ai-voice-over-generator/SKILL.md
source content

Getting Started

Send me your video or script and I'll handle the AI voiceover generation. Or just describe what you're after.

Try saying:

  • "generate a 2-minute product demo video with no audio into a 1080p MP4"
  • "generate a natural-sounding voiceover in English for this silent video"
  • "adding AI-generated voiceovers to silent or muted videos 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 <token>
    ,
    Content-Type: application/json
    , and body
    {"task_name":"project","language":"<detected>"}
    . 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.

AI Voice Over Generator — Generate Voiceovers for Any Video

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

A quick example: upload a 2-minute product demo video with no audio, type "generate a natural-sounding voiceover in English for this silent video", and you'll get a 1080p MP4 back in roughly 30-60 seconds. All rendering happens server-side.

Worth noting: shorter scripts produce more natural-sounding results — keep sentences under 20 words.

Matching Input to Actions

User prompts referencing ai voice over generator, aspect ratio, text overlays, or audio tracks get routed to the corresponding action via keyword and intent classification.

User says...ActionSkip 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.

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

HeaderValue
X-Skill-Source
ai-voice-over-generator
X-Skill-Version
frontmatter
version
X-Skill-Platform
auto-detect:
clawhub
/
cursor
/
unknown
from install path

All requests must include:

Authorization: Bearer <NEMO_TOKEN>
,
X-Skill-Source
,
X-Skill-Version
,
X-Skill-Platform
. Missing attribution headers will cause export to fail with 402.

API base:

https://mega-api-prod.nemovideo.ai

Create session: POST

/api/tasks/me/with-session/nemo_agent
— body
{"task_name":"project","language":"<lang>"}
— returns
task_id
,
session_id
.

Send message (SSE): POST

/run_sse
— body
{"app_name":"nemo_agent","user_id":"me","session_id":"<sid>","new_message":{"parts":[{"text":"<msg>"}]}}
with
Accept: text/event-stream
. Max timeout: 15 minutes.

Upload: POST

/api/upload-video/nemo_agent/me/<sid>
— file: multipart
-F "files=@/path"
, or URL:
{"urls":["<url>"],"source_type":"url"}

Credits: GET

/api/credits/balance/simple
— returns
available
,
frozen
,
total

Session state: GET

/api/state/nemo_agent/me/<sid>/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_<ts>","sessionId":"<sid>","draft":<json>,"output":{"format":"mp4","quality":"high"}}
. Poll GET
/api/render/proxy/lambda/<id>
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

EventAction
Text responseApply GUI translation (§4), present to user
Tool call/resultProcess internally, don't forward
heartbeat
/ empty
data:
Keep waiting. Every 2 min: "⏳ Still working..."
Stream closesProcess 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 saysYou 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 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=<id>
    , 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 → "generate a natural-sounding voiceover in English for this silent video" → Download MP4. Takes 30-60 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.

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "generate a natural-sounding voiceover in English for this silent 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.