Podcast Video Editing Software

Turn a 45-minute raw podcast recording with two speakers into 1080p polished podcast videos just by typing what you need. Whether it's editing raw podcast re...

Security Scan

The skill's requirements and runtime instructions are coherent with a cloud-based podcast video editing service, but it will upload your recordings and automatically request/store a service token — confirm the service and storage behavior before use.

Purpose & Capability

The skill only asks for a single service credential (NEMO_TOKEN) and its SKILL.md describes uploading media to a remote rendering backend; that matches the stated goal of cloud podcast video editing. One minor inconsistency: the registry metadata lists no required config paths, but the SKILL.md frontmatter includes a configPaths entry (~/.config/nemovideo/).

Instruction Scope

Runtime instructions focus on authenticating, creating a session, uploading media, sending edit commands, polling render status, and returning a download URL — all expected for this purpose. They explicitly instruct automatically obtaining an anonymous token via the nemovideo API if NEMO_TOKEN is not set and to store session_id and token for subsequent requests. This implies user files and metadata will be transmitted to an external service (nemovideo.ai), which is expected but important for privacy.

Install Mechanism

No install spec or code is included (instruction-only skill), so nothing will be written to disk by the skill itself during install. This minimizes install-time risk.

Credentials

Only one credential is required (NEMO_TOKEN) which is proportional to the described cloud API usage. The SKILL.md also describes auto-creating an anonymous token when none is present — the skill will contact an external API to obtain and then store a token. The exact storage location/permission model is not specified (and the registry metadata/configPaths are inconsistent), so confirm how/where tokens and session IDs are persisted.

Persistence & Privilege

The skill is not marked always:true and uses the platform's normal autonomous invocation settings. It does not request system-wide modifications or other skills' credentials. Autonomous invocation plus external network access increases blast radius if the backend were malicious, but that is expected for a cloud editing skill.

Assessment

This skill appears to do what it claims: it will upload your recordings to an external GPU-backed service (https://mega-api-prod.nemovideo.ai) and use a NEMO_TOKEN to authenticate. Before installing or using it: (1) verify the service/domain (nemovideo.ai) and check its privacy/TOS to understand how long uploads are stored and who can access them; (2) confirm where the skill stores the anonymous token/session_id (environment, config file, or memory) and whether those files are protected; (3) be cautious about uploading sensitive or confidential audio/video to a third-party service; (4) ask the skill author to resolve the metadata inconsistency around configPaths and to document token storage and deletion policies. If you need stronger assurances, request source code or an official homepage for independent review.

Getting Started

Share your raw podcast footage and I'll get started on AI podcast editing. Or just tell me what you're thinking.

Try saying:

• "edit my raw podcast footage"
• "export 1080p MP4"
• "remove filler words, trim silences, and"

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.

Podcast Video Editing Software — Edit and Export Podcast Videos

Send me your raw podcast footage and describe the result you want. The AI podcast editing runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload a 45-minute raw podcast recording with two speakers, type "remove filler words, trim silences, and add chapter title cards", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: splitting long episodes into segments before uploading speeds up processing significantly.

Matching Input to Actions

User prompts referencing podcast video editing software, 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.

Headers are derived from this file's YAML frontmatter. X-Skill-Source is podcast-video-editing-software, X-Skill-Version comes from the version field, and X-Skill-Platform is detected from the install path (~/.clawhub/ = clawhub, ~/.cursor/skills/ = cursor, otherwise unknown).

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

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 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

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "remove filler words, trim silences, and add chapter title cards" — 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 YouTube, Spotify, and podcast platforms.

Common Workflows

Quick edit: Upload → "remove filler words, trim silences, and add chapter title cards" → 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.