Hug Video Maker Free

Get animated hug video ready to post, without touching a single slider. Upload your photos or clips (JPG, PNG, MP4, MOV, up to 200MB), say something like "cr...

Security Scan

The skill's stated purpose (create hug videos via a cloud API) is plausible, but there are inconsistencies around credentials and metadata that warrant caution before installing.

Purpose & Capability

Requesting a NEMO_TOKEN credential is coherent with a cloud-rendering video service. However the SKILL.md frontmatter lists a local config path (~/.config/nemovideo/) even though the registry metadata earlier reported no config paths — that mismatch is unexplained and could indicate sloppy packaging or an omitted local access requirement.

Instruction Scope

Instructions are focused on remote API use (session creation, SSE, upload, export) and do not explicitly ask the agent to read arbitrary local files. They do instruct auto-setup: check NEMO_TOKEN in env, otherwise obtain an anonymous token by POSTing to the service. The skill also asks the agent to auto-detect platform from install path (which implies reading agent install path) and to include attribution headers on every request. No steps instruct exfiltration beyond use of the service endpoints, but the metadata/config-path discrepancy means the agent might be expected to access a local config directory that is not described elsewhere.

Install Mechanism

Instruction-only skill with no install spec and no code files — lowest install risk. Nothing is downloaded or written by an installer in the package itself.

Credentials

The skill declares a single primary credential (NEMO_TOKEN), which is proportionate for a cloud API. However, the SKILL.md also documents an anonymous-token flow (POST to /api/auth/anonymous-token) that will create a token if NEMO_TOKEN is missing. Declaring NEMO_TOKEN as 'required' while simultaneously providing an automated acquisition flow is inconsistent. The frontmatter's listed config path (~/.config/nemovideo/) increases the credential/secret surface but is not explained or justified elsewhere.

Persistence & Privilege

always:false and no install scripts are present. The skill instructs holding a session_id for the duration of an operation but does not request persistent, system-wide privileges or modifications to other skills. Autonomous invocation is enabled by default (normal) and not by itself a red flag here.

What to consider before installing

This skill mostly does what it says (calls a cloud rendering API) but has a few inconsistencies you should confirm before installing: (1) It lists NEMO_TOKEN as required yet describes an anonymous-token acquisition flow — ask whether you need to provide your own token or if the skill will always create one. (2) The SKILL.md frontmatter mentions a local config path (~/.config/nemovideo/) even though the registry listing did not — ask whether the skill will read or write files in that directory and why. (3) Uploaded photos/videos are sent to mega-api-prod.nemovideo.ai — confirm you are comfortable with that third-party handling your media and review their privacy terms. (4) Because the skill can auto-create tokens, check where/if those tokens are stored (in-memory only vs saved on disk/environment). If you want to be cautious, avoid providing a persistent NEMO_TOKEN in your environment and request clarification from the publisher about local config access and token storage before granting broader privileges.

Getting Started

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

Try saying:

• "create my photos or clips"
• "export 1080p MP4"
• "create a hug animation video from"

Quick Start Setup

This skill connects to a cloud processing backend. On first use, set up the connection automatically and let the user know ("Connecting...").

Token check: Look for NEMO_TOKEN in the environment. If found, skip to session creation. Otherwise:

• Generate a UUID as client identifier
• POST https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with X-Client-Id header
• Extract data.token from the response — this is your NEMO_TOKEN (100 free credits, 7-day expiry)

Session: POST https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Keep the returned session_id for all operations.

Let the user know with a brief "Ready!" when setup is complete. Don't expose tokens or raw API output.

Hug Video Maker Free — Create Hug Videos from Photos

Send me your photos or clips and describe the result you want. The AI hug video creation runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload two portrait photos of people, type "create a hug animation video from these two photos", and you'll get a 1080p MP4 back in roughly 30-60 seconds. All rendering happens server-side.

Worth noting: clear portrait photos with plain backgrounds produce the most realistic hug animations.

Matching Input to Actions

User prompts referencing hug video maker free, 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.

All calls go to https://mega-api-prod.nemovideo.ai. The main endpoints:

1. Session — POST /api/tasks/me/with-session/nemo_agent with {"task_name":"project","language":"<lang>"}. Gives you a session_id.
2. Chat (SSE) — POST /run_sse with session_id and your message in new_message.parts[0].text. Set Accept: text/event-stream. Up to 15 min.
3. Upload — POST /api/upload-video/nemo_agent/me/<sid> — multipart file or JSON with URLs.
4. Credits — GET /api/credits/balance/simple — returns available, frozen, total.
5. State — GET /api/state/nemo_agent/me/<sid>/latest — current draft and media info.
6. Export — POST /api/render/proxy/lambda with render ID and draft JSON. Poll GET /api/render/proxy/lambda/<id> every 30s for completed status and download URL.

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

Three attribution headers are required on every request and must match this file's frontmatter:

Header	Value
X-Skill-Source	hug-video-maker-free
X-Skill-Version	frontmatter version
X-Skill-Platform	auto-detect: clawhub / cursor / unknown from install path

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

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)

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

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.

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 "create a hug animation video from these two photos" — concrete instructions get better results.

Max file size is 200MB. Stick to JPG, PNG, MP4, MOV for the smoothest experience.

Export as MP4 for widest compatibility across social platforms and messaging apps.

Common Workflows

Quick edit: Upload → "create a hug animation video from these two photos" → 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.