Free Podcast Video

Get podcast video files ready to post, without touching a single slider. Upload your audio or video files (MP3, MP4, WAV, MOV, up to 500MB), say something li...

Security Scan

The skill's requests and runtime instructions are generally consistent with its stated purpose (uploading audio/video to a cloud rendering API using a NEMO_TOKEN), with only minor metadata/instruction mismatches to be aware of.

Purpose & Capability

The name/description (convert podcast audio to video) align with the runtime instructions: calls to a media-rendering API, upload endpoints, credits/status endpoints, and export endpoints. The required environment variable NEMO_TOKEN is the expected credential for a remote API.

Instruction Scope

Instructions stay within the video-rendering workflow: session creation, SSE message streaming, file upload, export/polling, and checking credits/state. They explicitly warn not to print tokens. One small inconsistency: the frontmatter metadata refers to a config path (~/.config/nemovideo/) and auto-detecting an install path for X-Skill-Platform, but SKILL.md never instructs the agent to read that config path; this should be clarified (it could be benign — e.g., an optional local config — but it is not documented in the runtime steps).

Install Mechanism

No install spec and no code files are present (instruction-only). Nothing is downloaded or executed locally by the skill spec itself.

Credentials

Only NEMO_TOKEN is required and serves the clear purpose of Bearer auth to the rendering API. However, the metadata also lists a configPaths entry (~/.config/nemovideo/) which could imply reading local configuration; the SKILL.md does not describe reading that path. Confirm whether the skill will access that directory and what it might contain before granting broad filesystem access.

Persistence & Privilege

The skill does not request always: true and makes no persistent system modifications in the instructions. It uses session tokens from the API but does not claim to write or modify other skills or system-wide agent settings.

Assessment

This skill appears to do what it says: upload audio/video to a cloud rendering API and return a produced MP4. Before installing or enabling it: 1) Confirm the source/trustworthiness of the endpoint (mega-api-prod.nemovideo.ai) and the skill author, since media files and session tokens are uploaded to that service. 2) Note it needs a NEMO_TOKEN (or it will request an anonymous token via the API); avoid providing high-privilege or long-lived secrets. 3) Ask the author to clarify the metadata reference to ~/.config/nemovideo/ and how/when the agent would access it — if the skill will read that directory, consider the privacy of any tokens stored there. 4) Understand that your media files will be transmitted to the remote service; check its privacy/retention policy if that matters. If you need stronger assurance, request a vetted source or official homepage/owner verification before enabling the skill.

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.

Free Podcast Video — Convert Podcast Audio to Video

This tool takes your audio or video files and runs AI podcast video creation through a cloud rendering pipeline. You upload, describe what you want, and download the result.

Say you have a 30-minute podcast audio recording in MP3 and want to turn my podcast audio into a video with captions and a waveform visual — the backend processes it in about 1-2 minutes and hands you a 1080p MP4.

Tip: shorter episode clips under 10 minutes process significantly faster and perform better on social platforms.

Matching Input to Actions

User prompts referencing free podcast 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.

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

Header	Value
X-Skill-Source	free-podcast-video
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

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.

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

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)

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 → "turn my podcast audio into a video with captions and a waveform visual" → 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 "turn my podcast audio into a video with captions and a waveform visual" — 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 Video, and social media.