Skills kling-ai-free

Name: kling-ai-free
Author: openclaw

install

source · Clone the upstream repo

git clone https://github.com/openclaw/skills

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/openclaw/skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/bwbernardweston18/kling-ai-free" ~/.claude/skills/openclaw-skills-kling-ai-free && rm -rf "$T"

OpenClaw · Install into ~/.openclaw/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/openclaw/skills "$T" && mkdir -p ~/.openclaw/skills && cp -r "$T/skills/bwbernardweston18/kling-ai-free" ~/.openclaw/skills/openclaw-skills-kling-ai-free && rm -rf "$T"

manifest: skills/bwbernardweston18/kling-ai-free/SKILL.md

Getting Started

Ready when you are. Drop your text or images here or describe what you want to make.

Try saying:

"generate a short text prompt or a single reference image into a 1080p MP4"
"generate a 5-second cinematic video clip from my product photo"
"generating short AI videos from text prompts or images for free for TikTok creators, marketers, social media managers"

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.

Kling AI Free — Generate AI Videos From Prompts

This tool takes your text or images and runs AI video generation through a cloud rendering pipeline. You upload, describe what you want, and download the result.

Say you have a short text prompt or a single reference image and want to generate a 5-second cinematic video clip from my product photo — the backend processes it in about 1-3 minutes and hands you a 1080p MP4.

Tip: shorter prompts with clear motion descriptions produce more consistent results.

Matching Input to Actions

User prompts referencing kling ai 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.

Include

Authorization: Bearer <NEMO_TOKEN>

and all attribution headers on every request — omitting them triggers a 402 on export.

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

```
X-Skill-Source
```
:
```
kling-ai-free
```
```
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 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

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

Reading the SSE Stream

Text events go straight to the user (after GUI translation). Tool calls stay internal. Heartbeats and empty

data:

lines mean the backend is still working — show "⏳ Still working..." every 2 minutes.

About 30% of edit operations close the stream without any text. When that happens, poll

/api/state

to confirm the timeline changed, then tell the user what was updated.

Draft JSON uses short keys:

for tracks,

tt

for track type (0=video, 1=audio, 7=text),

sg

for segments,

for duration in ms,

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 "generate a 5-second cinematic video clip from my product photo" — concrete instructions get better results.

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

Export as MP4 for widest compatibility across social platforms.

Common Workflows

Quick edit: Upload → "generate a 5-second cinematic video clip from my product photo" → 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.