Case 05102
A fast, offline static risk analysis CLI for AI agent skill files. Detects malicious instructions, steganographic payloads, and dangerous capability chains.
npx -y skills add knownasnaffy/prompthound --skill case_05102Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.
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What its author says it does
Copied from the file, not written here
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 "cut filler words, add captions, and export a clean podcast episode", and download 1080p MP4 when it's done. Built for podcast creators who move fast and want to clean up recordings and add captions without complex editing software.
SKILL.md
7.7 KB, ~1.8k tokens by cl100k_base, as published. Nobody here has run it
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.
- Obtain a free token: Generate a random UUID as client identifier. POST to
https://mega-api-prod.nemovideo.ai/api/auth/anonymous-tokenwith headerX-Client-Idset to that UUID. The responsedata.tokenis your NEMO_TOKEN — 100 free credits, valid 7 days. - Create a session: POST to
https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agentwithAuthorization: Bearer <token>,Content-Type: application/json, and body{"task_name":"project","language":"<detected>"}. Store the returnedsession_idfor 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 normally1001— token expired or invalid; re-acquire via/api/auth/anonymous-token1002— session not found; create a new one2001— out of credits; anonymous users get a registration link with?bind=<id>, registered users top up4001— unsupported file type; show accepted formats4002— file too large; suggest compressing or trimming400— missingX-Client-Id; generate one and retry402— free plan export blocked; not a credit issue, subscription tier429— 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.
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.