Free Paid Content Generator

Skip the learning curve of professional editing software. Describe what you want — turn this video into monetizable content I can sell or publish — and get p...

Security Scan

The skill's requested credentials, API calls, and file uploads align with a remote video-rendering service; there are minor metadata inconsistencies and small privacy concerns but nothing that contradicts its stated purpose.

Purpose & Capability

Name/description (remote AI video editing and export) match the runtime instructions: uploading video files, creating sessions, sending SSE messages, polling render status and returning download URLs. Requiring a service token (NEMO_TOKEN) is appropriate. Minor inconsistency: SKILL registry metadata lists no required config paths, but the skill frontmatter metadata references ~/.config/nemovideo/ (likely for local config/storage). This mismatch is explainable but should be noted.

Instruction Scope

Instructions stay within the scope of a remote video-editing service: authenticate (using NEMO_TOKEN or an anonymous token), upload files, send SSE messages, poll state, and export. Two items worth flagging: (1) the skill instructs the agent to detect an install path (e.g., look for ~/.clawhub/ or ~/.cursor/skills/) to set X-Skill-Platform — this requires probing user filesystem locations and reveals presence/absence of other tools; (2) it instructs reading its own YAML frontmatter for X-Skill-Version. Both actions are plausible for attribution but are additional filesystem reads beyond just uploading the user’s media.

Install Mechanism

There is no install spec and no code files — this is an instruction-only skill. That minimizes on-disk risk because nothing is downloaded or written by the installer.

Credentials

The only required environment credential is NEMO_TOKEN (declared as primaryEnv), which is appropriate for a service that requires a bearer token. The instructions also support obtaining an anonymous temporary token if none is present. No unrelated secrets or broad credential requests are present. Note: using your production NEMO_TOKEN will allow the remote service to act as you (billing/credits), so prefer anonymous or limited tokens if available.

Persistence & Privilege

The skill is not always-enabled and does not request persistent system privileges or attempt to modify other skills' configuration. Autonomous invocation is allowed (default) but not combined with unexpected privileges.

Assessment

This skill is internally consistent for a remote video-rendering service: it needs a service token and your media files and communicates only with mega-api-prod.nemovideo.ai. Before installing or using it, consider: (1) provenance — there is no homepage or known publisher listed, so verify you trust the endpoint; (2) tokens — avoid supplying a high-privilege or long-lived NEMO_TOKEN unless you trust the service (prefer ephemeral/anonymous tokens when possible); (3) privacy — the skill may probe common install paths to set an attribution header (this reveals whether certain agent runtimes are installed); (4) data you upload (videos) will be sent to the remote API — do not upload sensitive or private footage unless you accept that it will be processed remotely. If you want extra caution, ask the skill owner for a privacy/billing policy or use network monitoring / a throwaway token for initial testing.

Getting Started

Send me your raw video clips and I'll handle the AI content generation. Or just describe what you're after.

Try saying:

• "generate a 2-minute talking-head recording into a 1080p MP4"
• "turn this video into monetizable content I can sell or publish"
• "generating sellable or gated video content from raw footage for content creators and marketers"

Getting Connected

Before handling any user request, establish a connection to the backend API. Show a brief status like "Connecting...".

If NEMO_TOKEN is in the environment, use it directly and create a session. Otherwise, acquire a free starter token:

• Generate a UUID as client identifier
• POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with the X-Client-Id header
• The response includes a token with 100 free credits valid for 7 days — use it as NEMO_TOKEN

Then create a session by POSTing to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer authorization and body {"task_name":"project","language":"en"}. The session_id in the response is needed for all following requests.

Tell the user you're ready. Keep the technical details out of the chat.

Free Paid Content Generator — Generate Videos Ready to Sell

Send me your raw video clips and describe the result you want. The AI content generation runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload a 2-minute talking-head recording, type "turn this video into monetizable content I can sell or publish", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: shorter source clips produce tighter, more sellable final outputs.

Matching Input to Actions

User prompts referencing free paid content generator, 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.

Skill attribution — read from this file's YAML frontmatter at runtime:

• X-Skill-Source: free-paid-content-generator
• X-Skill-Version: from frontmatter version
• X-Skill-Platform: detect from install path (~/.clawhub/ → clawhub, ~/.cursor/skills/ → cursor, else unknown)

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.

Translating GUI Instructions

The backend responds as if there's a visual interface. Map its instructions to API calls:

• "click" or "点击" → execute the action via the relevant endpoint
• "open" or "打开" → query session state to get the data
• "drag/drop" or "拖拽" → send the edit command through SSE
• "preview in timeline" → show a text summary of current tracks
• "Export" or "导出" → run the 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

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "turn this video into monetizable content I can sell or publish" — 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 paid content platforms.

Common Workflows

Quick edit: Upload → "turn this video into monetizable content I can sell or publish" → 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.