Podcast Video Camera

Get polished podcast videos ready to post, without touching a single slider. Upload your raw footage (MP4, MOV, AVI, WebM, up to 500MB), say something like "...

Security Scan

The skill's behavior mostly matches a cloud-based video-editing tool (it uploads media and uses a single service token), but there are small inconsistencies and unexplained accesses (config path / install-path auto-detection) that you should confirm before installing or using it.

Purpose & Capability

Name/description align with instructions: cloud GPU-based AI video editing that uploads media and returns processed files. Requesting a single service token (NEMO_TOKEN) is reasonable for this purpose. However, the SKILL.md frontmatter lists a config path (~/.config/nemovideo/) while the registry metadata stated no required config paths — this mismatch is unexpected and should be clarified.

Instruction Scope

Runtime instructions stay within the editing use case (obtain/use a NEMO_TOKEN, create session, upload video, poll render status, download output). They direct the agent to POST user files and use SSE for streaming, which is appropriate for a cloud edit service. A minor scope creep: the skill asks to auto-detect 'X-Skill-Platform' from the install path, which implies reading the agent's install path or environment — not strictly necessary for editing and worth confirming.

Install Mechanism

Instruction-only skill with no install spec and no code files; nothing is written to disk by an installer. This is the lowest-risk install model.

Credentials

Only one credential is requested (NEMO_TOKEN), which is reasonable. The SKILL.md will auto-acquire an anonymous token if none is provided, so user secrets are not required. However, the frontmatter's configPaths entry (~/.config/nemovideo/) suggests the skill may try to read a local config directory (contradicting registry data). That could expose local files if true — ask whether that path is actually accessed and why.

Persistence & Privilege

Skill does not request 'always: true' and has no install actions that persist on disk. Autonomous invocation is allowed (platform default) but there is no elevated persistence or modification of other skills.

What to consider before installing

This skill appears to be a cloud-based video-editing front end that uploads your media to nemovideo.ai and returns edited files. Before using it, confirm: 1) The service domain (mega-api-prod.nemovideo.ai) is the official provider you expect and its privacy/retention policy is acceptable for your content, since your media will be uploaded off-device. 2) Whether the skill actually reads the suggested local config path (~/.config/nemovideo/) or the agent install path — if so, ask what data is read and why. 3) That no other sensitive credentials (AWS, GitHub, etc.) are required — the skill only needs NEMO_TOKEN and can create an anonymous token if you prefer not to supply one. Note that this is an instruction-only skill with no code for static scanning; absence of scan findings does not guarantee safety. If you need stronger guarantees, request the skill owner/source, a privacy/terms link, or an implementation that runs locally instead of uploading data to a remote API.

Getting Started

Got raw footage to work with? Send it over and tell me what you need — I'll take care of the AI video editing.

Try saying:

• "edit a 60-minute podcast recording with two hosts on camera into a 1080p MP4"
• "cut filler words, add captions, and export a clean podcast episode"
• "editing podcast recordings into publish-ready video episodes for podcast creators"

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 Camera — Edit and Export Podcast Videos

Drop your raw footage in the chat and tell me what you need. I'll handle the AI video editing on cloud GPUs — you don't need anything installed locally.

Here's a typical use: you send a a 60-minute podcast recording with two hosts on camera, ask for cut filler words, add captions, and export a clean podcast episode, 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 recordings into segments before uploading speeds up processing.

Matching Input to Actions

User prompts referencing podcast video camera, 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.

Every API call needs Authorization: Bearer <NEMO_TOKEN> plus the three attribution headers above. If any header is missing, exports return 402.

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

Header	Value
X-Skill-Source	podcast-video-camera
X-Skill-Version	frontmatter version
X-Skill-Platform	auto-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 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

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.

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 "cut filler words, add captions, and export a clean podcast episode" — 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 podcast video platforms.

Common Workflows

Quick edit: Upload → "cut filler words, add captions, and export a clean podcast episode" → 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.