Social Media Ai Video Maker

Skip the learning curve of professional editing software. Describe what you want — create a 30-second Instagram reel with transitions, music, and captions —...

Security Scan

The skill's requested token and API interactions are consistent with an online video-rendering service; no large mismatches between purpose and behavior were found, though there are a few small inconsistencies and privacy considerations to review before installing.

Purpose & Capability

Name/description (cloud video creation) align with requesting a single service token (NEMO_TOKEN) and talking to nemovideo.ai. Minor inconsistency: the registry metadata listed no required config paths, but the SKILL.md frontmatter mentions a config path (~/.config/nemovideo/). That mismatch should be clarified but does not itself indicate malicious intent.

Instruction Scope

SKILL.md instructs the agent to obtain (or generate) a bearer token, create a session, upload media, stream SSE messages, and request renders from mega-api-prod.nemovideo.ai — all expected for a cloud video service. The instructions do not direct the agent to read unrelated system files or other credentials, nor to post data to unrelated external endpoints.

Install Mechanism

Instruction-only skill with no install spec and no code files. This is the lowest-risk install mechanism; nothing will be written to disk by an installer step as part of skill installation.

Credentials

Only a single credential (NEMO_TOKEN) is required, which is proportionate for a cloud-rendering service. Note: the token grants API access to upload media and start renders—treat it as sensitive. Also note the SKILL.md mentions storing/using a token and a config path (~/.config/nemovideo/) even though the registry header said no config paths; clarify where tokens/session state will be persisted.

Persistence & Privilege

Skill is not forced always-on and uses default autonomous-invocation settings. It expects to save session_id and tokens for session management (normal). No indication it modifies other skills or system-wide agent settings.

Assessment

This skill appears to do what it says: it uploads media to nemovideo.ai and requests cloud renders using a single API token (NEMO_TOKEN). Before installing or enabling it, consider: (1) Keep NEMO_TOKEN private — it allows uploads and renders and could be used to access any data you send to the service. (2) Do not upload sensitive or private videos unless you trust the service and have read its privacy/retention policy. (3) Clarify the config-path inconsistency: SKILL.md references ~/.config/nemovideo/ but the registry metadata lists no config paths — ask the author where session tokens are stored and for how long. (4) Verify the API domain (mega-api-prod.nemovideo.ai) and confirm this is the official endpoint for the service. (5) If you need higher assurance, request source, homepage, or documentation from the author and verify terms/branding; absence of a homepage is a reason to be cautious.

Getting Started

Ready when you are. Drop your images or clips here or describe what you want to make.

Try saying:

• "create five product photos and a logo file into a 1080p MP4"
• "create a 30-second Instagram reel with transitions, music, and captions"
• "generating ready-to-post videos for Instagram, TikTok, and YouTube for social media creators and marketers"

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.

Social Media AI Video Maker — Create and Export Social Media Videos

Drop your images or clips in the chat and tell me what you need. I'll handle the AI video creation on cloud GPUs — you don't need anything installed locally.

Here's a typical use: you send a five product photos and a logo file, ask for create a 30-second Instagram reel with transitions, music, and captions, 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 — vertical 9:16 ratio works best for TikTok and Reels output.

Matching Input to Actions

User prompts referencing social media ai video maker, 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.

Base URL: https://mega-api-prod.nemovideo.ai

Endpoint	Method	Purpose
/api/tasks/me/with-session/nemo_agent	POST	Start a new editing session. Body: {"task_name":"project","language":"<lang>"}. Returns session_id.
/run_sse	POST	Send a user message. Body includes app_name, session_id, new_message. Stream response with Accept: text/event-stream. Timeout: 15 min.
/api/upload-video/nemo_agent/me/<sid>	POST	Upload a file (multipart) or URL.
/api/credits/balance/simple	GET	Check remaining credits (available, frozen, total).
/api/state/nemo_agent/me/<sid>/latest	GET	Fetch current timeline state (draft, video_infos, generated_media).
/api/render/proxy/lambda	POST	Start export. Body: {"id":"render_<ts>","sessionId":"<sid>","draft":<json>,"output":{"format":"mp4","quality":"high"}}. Poll status every 30s.

Accepted file types: mp4, mov, avi, webm, mkv, jpg, png, gif, webp, mp3, wav, m4a, aac.

Headers are derived from this file's YAML frontmatter. X-Skill-Source is social-media-ai-video-maker, 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).

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.

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

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)

Common Workflows

Quick edit: Upload → "create a 30-second Instagram reel with transitions, music, and captions" → 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 "create a 30-second Instagram reel with transitions, music, and captions" — concrete instructions get better results.

Max file size is 500MB. Stick to MP4, MOV, JPG, PNG for the smoothest experience.

Export as MP4 with H.264 codec for best compatibility across all social platforms.