Ai Video Generator Free Banana

Turn a short text description or a single banana product photo into 1080p AI generated video just by typing what you need. Whether it's generating short free...

Security Scan

The skill's runtime instructions generally match a remote AI video service, but there are inconsistencies in its metadata and a few privacy-sensitive behaviors (automatic token creation, reading install/config paths, uploading local files) that you should review before installing.

Purpose & Capability

Name/description match the actions described (create sessions, upload media, render on cloud GPUs). Requested env var NEMO_TOKEN is appropriate for a remote API. However the SKILL.md frontmatter lists a config path (~/.config/nemovideo/) that the registry metadata did not, which is an inconsistency worth clarifying.

Instruction Scope

The instructions explicitly tell the agent to: obtain or use a bearer token, create/stash session IDs, read the skill's YAML frontmatter for attribution headers, detect the install path to set X-Skill-Platform, and upload local files (multipart @/path). Those actions require filesystem access and will transmit user files and session tokens to an external service. This is expected for a cloud video generator, but it meaningfully expands the agent's scope (accessing local files and config paths).

Install Mechanism

No install spec or downloaded code — lowest install risk. The only runtime risk is network I/O to an external API (https://mega-api-prod.nemovideo.ai) which is expected for this type of skill.

Credentials

Only NEMO_TOKEN is required, which fits a remote rendering service. But the SKILL.md frontmatter also references a config path (~/.config/nemovideo/) and the runtime expects to read/derive install-path-based headers; those are not declared in the registry metadata. Requiring access to user config paths or local files increases privilege and should be justified.

Persistence & Privilege

The skill is not always-enabled and doesn't request elevated platform permissions. It does instruct storing session_id for the session lifecycle, but there is no instruction to modify other skills or system settings.

What to consider before installing

This skill appears to be a thin integration with an external video-rendering API (nemovideo.ai). Before installing: (1) confirm the vendor/domain is trustworthy (no homepage or source is provided here), (2) be aware the skill will upload any images or files you give it to the remote service and may generate an anonymous bearer token if you don't provide NEMO_TOKEN, (3) ask the author to explain the mismatched metadata (SKILL.md frontmatter lists ~/.config/nemovideo/ and install-path detection but the registry metadata did not), and (4) avoid storing a system-wide NEMO_TOKEN unless you trust the service, and do not send sensitive files. If you need higher assurance, request the skill's source or an allowlist of exact filesystem paths it will access and a privacy/data-retention policy from the service operator.

Getting Started

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

Try saying:

• "generate my text or images"
• "export 1080p MP4"
• "generate a free short video clip"

First-Time Connection

When a user first opens this skill, connect to the processing backend automatically. Briefly let them know (e.g. "Setting up...").

Authentication: Check if NEMO_TOKEN is set in the environment. If it is, skip to step 2.

1. Obtain a free token: Generate a random UUID as client identifier. POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id set to that UUID. The response data.token is your NEMO_TOKEN — 100 free credits, valid 7 days.
2. Create a session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Authorization: Bearer <token>, Content-Type: application/json, and body {"task_name":"project","language":"<detected>"}. Store the returned session_id for all subsequent requests.

Keep setup communication brief. Don't display raw API responses or token values to the user.

AI Video Generator Free Banana — Generate Free AI Videos Instantly

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

A quick example: upload a short text description or a single banana product photo, type "generate a free short video clip featuring a banana for my food blog", and you'll get a 1080p MP4 back in roughly 30-60 seconds. All rendering happens server-side.

Worth noting: simple single-subject prompts like a banana produce cleaner results than complex scenes.

Matching Input to Actions

User prompts referencing ai video generator free banana, 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 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.

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

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

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.

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

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.

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 → "generate a free short video clip featuring a banana for my food blog" → 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.

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "generate a free short video clip featuring a banana for my food blog" — concrete instructions get better results.

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

Export as MP4 for widest compatibility.