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Best Podcast Video

v1.0.0

convert audio or video files into polished podcast videos with this skill. Works with MP3, MP4, WAV, MOV files up to 500MB. podcasters use it for converting...

0· 56·0 current·0 all-time

Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for tk8544-b/best-podcast-video.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Best Podcast Video" (tk8544-b/best-podcast-video) from ClawHub.
Skill page: https://clawhub.ai/tk8544-b/best-podcast-video
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Required env vars: NEMO_TOKEN
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

Bare skill slug

openclaw skills install best-podcast-video

ClawHub CLI

Package manager switcher

npx clawhub@latest install best-podcast-video
Security Scan
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OpenClawOpenClaw
Benign
medium confidence
Purpose & Capability
The name/description (convert audio/video to 1080p MP4) matches the SKILL.md instructions: create a session, upload files, request renders, and poll for download URLs on the nemo API. The single declared credential (NEMO_TOKEN) is appropriate for an external processing API.
Instruction Scope
Instructions stay within the stated purpose (session creation, SSE message streaming, multipart file uploads, render/poll workflow). They explicitly tell the agent to upload user-provided media to https://mega-api-prod.nemovideo.ai and to create an anonymous token if none is provided. This is expected for a cloud-rendering service but means user files and metadata will be transmitted off-device (privacy consideration). The SKILL.md also asks the agent to auto-detect platform/install path for a header value — that requires reading agent/install path information but is narrow in scope.
Install Mechanism
No install spec and no code files — instruction-only skill. Nothing will be written to disk by an installer. This is the lowest install risk.
Credentials
Only one env var (NEMO_TOKEN) is required, which is proportional to using an external API. Minor inconsistency: the registry summary listed no required config paths, but the SKILL.md frontmatter metadata references a config path (~/.config/nemovideo/). This mismatch should be clarified but is not itself a high-risk issue.
Persistence & Privilege
always:false and disable-model-invocation:false (normal default). The skill does not request permanent/always-included status or elevated privileges over other skills.
Assessment
This skill appears to do what it says: it uploads audio/video to an external rendering API and returns a downloadable MP4. Before installing or using it, consider: (1) Privacy — your media (audio, transcripts, captions) will be sent to https://mega-api-prod.nemovideo.ai; do not send sensitive or private recordings unless you trust this service. (2) Token handling — provide a NEMO_TOKEN only if you trust the service; if omitted, the skill requests an anonymous token (100 credits, 7-day expiry). (3) Metadata mismatch — the SKILL.md references a local config path (~/.config/nemovideo/) while registry metadata did not; ask the publisher to clarify. (4) Unknown origin — there is no homepage and the owner is an opaque ID; prefer skills from known/published vendors for production or sensitive work. If you proceed, consider using an anonymous token and test with non-sensitive media first.

Like a lobster shell, security has layers — review code before you run it.

Runtime requirements

🎙️ Clawdis
EnvNEMO_TOKEN
Primary envNEMO_TOKEN
latestvk97610kn7m98k5yxq0rfxw49hh84p4fc
56downloads
0stars
1versions
Updated 2w ago
v1.0.0
MIT-0

Getting Started

Share your audio or video files and I'll get started on AI podcast video creation. Or just tell me what you're thinking.

Try saying:

  • "convert my audio or video files"
  • "export 1080p MP4"
  • "turn my podcast audio into a"

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: <uuid>. 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.

Best Podcast Video — Convert Podcast Audio to Video

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

Here's a typical use: you send a a 30-minute podcast audio recording, ask for turn my podcast audio into a video with waveform animation and captions, 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 — splitting long episodes into shorter clips gets more engagement on social platforms.

Matching Input to Actions

User prompts referencing best podcast video, 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.

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.

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

HeaderValue
X-Skill-Sourcebest-podcast-video
X-Skill-Versionfrontmatter version
X-Skill-Platformauto-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":"<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.

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

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

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)

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "turn my podcast audio into a video with waveform animation and captions" — concrete instructions get better results.

Max file size is 500MB. Stick to MP3, MP4, WAV, MOV for the smoothest experience.

Export as MP4 for widest compatibility across YouTube, Spotify, and social media.

Common Workflows

Quick edit: Upload → "turn my podcast audio into a video with waveform animation and captions" → 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.

Comments

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