Instagram Photo Video Maker

Cloud-based instagram-photo-video-maker tool that handles turning photo collections into Instagram reels or stories. Upload JPG, PNG, HEIC, WebP files (up to...

Security Scan

The skill's requests and runtime instructions are coherent with a cloud photo→video rendering service: it asks for a single service token, describes service endpoints, and does not attempt to access unrelated secrets or install arbitrary code.

Purpose & Capability

The skill is a cloud-based photo→video renderer and requires a NEMO_TOKEN and network access to mega-api-prod.nemovideo.ai, which matches the stated purpose. One inconsistency: the skill's YAML frontmatter declares a config path (~/.config/nemovideo/), but the registry metadata lists no required config paths—this is a small mismatch worth noting but explainable (the skill may optionally read that config dir).

Instruction Scope

The SKILL.md instructs the agent to: obtain/use a NEMO_TOKEN, optionally generate an anonymous token via the service API, create sessions, upload user files to the service, and stream SSE responses. It also instructs the agent to read the skill's YAML frontmatter (its own file) and detect install paths (~/.clawhub/, ~/.cursor/) to populate attribution headers. These filesystem reads are limited and related to attribution, but reading home config/install paths is privacy-sensitive—it's within the skill's described behavior but users should be aware uploads and some local path inspection occur.

Install Mechanism

No install spec or code is present (instruction-only), so nothing is written to disk or pulled during install. This is the lowest-risk install model.

Credentials

Only one credential is declared (NEMO_TOKEN) and it is the primaryEnv; the instructions also support creating an anonymous token via the service API if no token is provided. There are no other unrelated credentials or broad environment requirements. The frontmatter's mention of a config path is the only extra I/O request and is plausibly used for optional local config.

Persistence & Privilege

The skill is not always-on (always: false) and uses normal autonomous-invocation defaults. It requires saving session_id and token for session management (expected for this service) but does not request system-wide settings or other skills' configs.

Assessment

This skill appears to do what it says, but it uploads your images and uses an external API (mega-api-prod.nemovideo.ai). Before installing/providing a permanent NEMO_TOKEN: 1) Verify you trust the service owner (no homepage is listed and owner ID is unknown). 2) Prefer using the anonymous token flow (the skill documents it) instead of pasting a long-lived token you care about. 3) Be aware the skill may read small local paths for attribution (~/.config/nemovideo/, install paths) — avoid running it in environments with sensitive local files. 4) Test with non-sensitive/dummy images first and confirm expected behavior, data retention, and billing/credits. 5) If you need stronger assurance, ask the publisher for a homepage/source repo and privacy/security documentation before providing any real tokens or private media.

Getting Started

Share your photos and images and I'll get started on AI video creation. Or just tell me what you're thinking.

Try saying:

• "turn my photos and images"
• "export 1080p MP4"
• "turn my photos into a 30-second"

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.

Instagram Photo Video Maker — Turn Photos into Instagram Videos

Drop your photos and images 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 or lifestyle photos, ask for turn my photos into a 30-second Instagram reel with music and transitions, and about 30-60 seconds 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 Reels and Stories output.

Matching Input to Actions

User prompts referencing instagram photo 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.

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

• X-Skill-Source: instagram-photo-video-maker
• 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 Handling

Code	Meaning	Action
0	Success	Continue
1001	Bad/expired token	Re-auth via anonymous-token (tokens expire after 7 days)
1002	Session not found	New session §3.0
2001	No credits	Anonymous: show registration URL with ?bind=<id> (get <id> from create-session or state response when needed). Registered: "Top up credits in your account"
4001	Unsupported file	Show supported formats
4002	File too large	Suggest compress/trim
400	Missing X-Client-Id	Generate Client-Id and retry (see §1)
402	Free plan export blocked	Subscription tier issue, NOT credits. "Register or upgrade your plan to unlock export."
429	Rate limit (1 token/client/7 days)	Retry in 30s 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 "turn my photos into a 30-second Instagram reel with music and transitions" — concrete instructions get better results.

Max file size is 200MB. Stick to JPG, PNG, HEIC, WebP for the smoothest experience.

Export as MP4 for direct upload compatibility with Instagram.

Common Workflows

Quick edit: Upload → "turn my photos into a 30-second Instagram reel with music and transitions" → Download MP4. Takes 30-60 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.