Ai Social Copy Generator

Skip the learning curve of professional editing software. Describe what you want — write social media captions for Instagram, Twitter, and LinkedIn based on...

Security Scan

The skill's declared purpose (generate social captions and edited videos) matches the network calls and credential it requests, but there are a few small metadata inconsistencies and privacy considerations to review before use.

Purpose & Capability

The skill claims to generate social captions and processed videos and it only requests a service token (NEMO_TOKEN) and network access to mega-api-prod.nemovideo.ai, which is consistent. However, the SKILL.md frontmatter lists a config path (~/.config/nemovideo/) while the registry metadata earlier shows no required config paths — this mismatch should be reconciled.

Instruction Scope

Runtime instructions are narrowly focused on creating/using a session, uploading video/media, streaming SSE messages, polling render status, and returning download URLs. The agent is instructed to use NEMO_TOKEN (or obtain an anonymous token via the provided endpoint) and to include attribution headers. The instructions do not ask the agent to read arbitrary user files or unrelated environment variables.

Install Mechanism

This is an instruction-only skill with no install spec or code files, so nothing is written to disk by an installer. That is the lowest-risk install mechanism.

Credentials

The only required credential is NEMO_TOKEN (primaryEnv), which is appropriate for calling the described API. The skill also describes generating an anonymous token if NEMO_TOKEN is absent. The small concern is the SKILL.md's additional configPaths entry (~/.config/nemovideo/), which is not listed in the registry metadata — reading that config path would grant access to potentially sensitive local tokens/config, so the mismatch should be clarified.

Persistence & Privilege

always is false and there is no install hook requesting permanent system presence. The skill will store session_id and use bearer tokens for API calls (normal for a remote-processing service). Autonomous invocation is allowed (platform default) but that by itself is expected.

Assessment

This skill will upload any videos or media you send to an external service (https://mega-api-prod.nemovideo.ai) and requires a NEMO_TOKEN (or will obtain a short-lived anonymous token) to operate. Before installing/using it: (1) confirm you trust the nemovideo service for your content (do not upload sensitive or private videos until you verify privacy/retention policies); (2) reconcile the small metadata mismatch — SKILL.md references ~/.config/nemovideo/ while the registry metadata does not — to understand whether local config or tokens will be read; (3) prefer using the anonymous token flow for testing or a limited-scope token rather than a long-lived credential; and (4) test with non-sensitive sample media to confirm the behavior and headers it sends (attribution headers and Authorization) match your expectations.

Getting Started

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

Try saying:

• "generate a 60-second product demo video into a 1080p MP4"
• "write social media captions for Instagram, Twitter, and LinkedIn based on this video"
• "generating platform-specific social copy from video content for 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.

AI Social Copy Generator — Generate Social Captions from Video

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

Here's a typical use: you send a a 60-second product demo video, ask for write social media captions for Instagram, Twitter, and LinkedIn based on this video, and about 20-40 seconds later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.

One thing worth knowing — shorter videos under 90 seconds produce more focused, usable social copy.

Matching Input to Actions

User prompts referencing ai social copy 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.

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.

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

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

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

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)

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "write social media captions for Instagram, Twitter, and LinkedIn based on this video" — 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 social platforms.

Common Workflows

Quick edit: Upload → "write social media captions for Instagram, Twitter, and LinkedIn based on this video" → Download MP4. Takes 20-40 seconds 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.