kling-ai-30

Skip the learning curve of professional editing software. Describe what you want — generate a 30-second cinematic video from this image with slow camera movement — and get AI generated videos back in 1-3 minutes. Upload MP4, JPG, PNG, WebM files up to 200MB, and the AI handles AI video generation automatically. Ideal for content creators who want to create short AI videos without filming real footage.

Safety Notice

This listing is from the official public ClawHub registry. Review SKILL.md and referenced scripts before running.

Copy this and send it to your AI assistant to learn

Install skill "kling-ai-30" with this command: npx skills add tk8544-b/kling-ai-30

Getting Started

Send me your text prompts or images and I'll handle the AI video generation. Or just describe what you're after.

Try saying:

  • "generate a photo of a mountain landscape into a 1080p MP4"
  • "generate a 30-second cinematic video from this image with slow camera movement"
  • "generating 30-second AI videos from images or text prompts for content creators"

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.

Kling AI 30-Second Video — Generate 30-Second AI Videos

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

A quick example: upload a photo of a mountain landscape, type "generate a 30-second cinematic video from this image with slow camera movement", and you'll get a 1080p MP4 back in roughly 1-3 minutes. All rendering happens server-side.

Worth noting: 30-second clips use more credits than shorter ones — preview at 5 seconds first to check motion quality.

Matching Input to Actions

User prompts referencing kling ai 30, aspect ratio, text overlays, or audio tracks get routed to the corresponding action via keyword and intent classification.

User says...ActionSkip 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.

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

Headers are derived from this file's YAML frontmatter. X-Skill-Source is kling-ai-30, 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).

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 Handling

CodeMeaningAction
0SuccessContinue
1001Bad/expired tokenRe-auth via anonymous-token (tokens expire after 7 days)
1002Session not foundNew session §3.0
2001No creditsAnonymous: show registration URL with ?bind=<id> (get <id> from create-session or state response when needed). Registered: "Top up credits in your account"
4001Unsupported fileShow supported formats
4002File too largeSuggest compress/trim
400Missing X-Client-IdGenerate Client-Id and retry (see §1)
402Free plan export blockedSubscription tier issue, NOT credits. "Register or upgrade your plan to unlock export."
429Rate limit (1 token/client/7 days)Retry in 30s once

Backend Response Translation

The backend assumes a GUI exists. Translate these into API actions:

Backend saysYou 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

SSE Event Handling

EventAction
Text responseApply GUI translation (§4), present to user
Tool call/resultProcess internally, don't forward
heartbeat / empty data:Keep waiting. Every 2 min: "⏳ Still working..."
Stream closesProcess 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 30-second cinematic video from this image with slow camera movement" → Download MP4. Takes 1-3 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 "generate a 30-second cinematic video from this image with slow camera movement" — concrete instructions get better results.

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

Export as MP4 for widest compatibility across social platforms.

Source Transparency

This detail page is rendered from real SKILL.md content. Trust labels are metadata-based hints, not a safety guarantee.

Related Skills

Related by shared tags or category signals.

General

Huo15 Openclaw Enhance

火一五·克劳德·龙虾增强插件 v5.7.8 — 全面适配 openclaw 2026.4.24:peerDep ^4.24 + build/compat 同步到 4.24 + 14 处 api.on 全部去掉 as any 改成 typed hook(hookName 联合类型 + handler 自动推断 Pl...

Registry SourceRecently Updated
General

Content Trend Analyzer

Aggregates and analyzes content trends across platforms to identify hot topics, user intent, content gaps, and generates data-driven article outlines.

Registry SourceRecently Updated
General

Prompt Debugger

Debug prompts that produce unexpected AI outputs — diagnose failure modes, identify ambiguity and conflicting instructions, test variations, compare model re...

Registry SourceRecently Updated
General

Indie Maker News

独行者 Daily - 变现雷达。读对一条新闻,少走一年弯路。每天5分钟,给创业者装上商业雷达。聚焦一人公司、副业、创业变现资讯,智能分类,行动导向。用户下载即能用,无需本地部署!

Registry SourceRecently Updated