Glass Cut Video

Other

Generate satisfying vertical short videos of glass cutting and shattering (WeryAI): text-to-video or animate a glass photo into cuts, crack spread, and break motion for Douyin/Kuaishou-style ASMR. Use when you need glass cutting video, glass shatter clip, scratch-and-crack ASMR, or users ask for clean slices, crack propagation, or glass ASMR sound.

Install

openclaw skills install glass-cut-video

Glass cutting & shatter videos

Built for satisfying-content creators. Whether it’s the perfection of a straight cut, the rush of tempered glass exploding, or stained glass glowing in the light—you can go from one line of text or one image to a ready-to-post 9:16 clip.

Dependencies: scripts/video_gen.js in this folder + WERYAI_API_KEY in the environment + Node.js 18+. No other Cursor skills required.

Prerequisites

WERYAI_API_KEY must be set in the environment before running video_gen.js.
Node.js 18+ is required. Image inputs must be public https URLs (no local file paths).
Each successful wait run consumes WeryAI credits; re-running creates new paid tasks.

Security, secrets, and API hosts

WERYAI_API_KEY: Treat as a secret. Only configure it if you trust this skill's source; it is listed in OpenClaw metadata as requires.env / primaryEnv so installers know it is mandatory at runtime (never commit it inside the skill package).
API hosts (fixed in video_gen.js): Video tasks use https://api.weryai.com; the models list uses https://api-growth-agent.weryai.com. Only WERYAI_API_KEY is read from the environment—do not rely on URL-related environment variables.
Higher assurance: Run generation in a short-lived or isolated environment (separate account or container), and review scripts/video_gen.js (HTTPS submit + poll loop) before production use.

Prompt expansion (mandatory)

video_gen.js does not expand prompts. Before every wait --json, turn the user's short or vague brief into a full English production prompt.

When: The user gives only keywords, one line, or loose intent—or asks for richer video language. Exception: They paste a finished long prompt within the model's prompt_length_limit and ask you not to rewrite; still show the full text in the confirmation table.

Always add (video language): shot scale and angle; camera move or lock-off; light quality and motivation; subject action paced to duration; one clear payoff for this niche; state 9:16 vertical when this skill defaults to vertical.

Length: Obey prompt_length_limit for the chosen model_key when this doc lists it; trim filler adjectives before removing core action, lens, or light clauses.

Confirmation: The pre-submit table must include the full expanded prompt (never a one-line summary). Wait for confirm or edits.

Niche checklist

Glass grammar: score line, crack propagation, snap, shards, tempered burst, or stained-glass glow—pick one clear beat.
Macro & light: caustics, speculars, transmitted color; ASMR glass tone if audio on.
Safety tone: stylized satisfying break, not real injury context.

### Example prompts at the top of this file are short triggers only—always expand from the user's actual request.

Workflow

Confirm the request matches this skill (text-to-video and/or image-to-video as documented).
Collect the user's brief, optional image URL(s), tier (best / good / fast) or an explicit model key.
Expand prompt (mandatory): Unless the user supplied a finished long prompt and explicitly asked not to rewrite it, expand the brief into a full English production prompt using ## Prompt expansion (mandatory) below. Do not call the API with only the user's minimal words.
Check the expanded prompt against the selected model's prompt_length_limit in the frozen tables in this document (when present); shorten if needed.
Verify duration, aspect_ratio, resolution, generate_audio, negative_prompt, and other fields against the frozen tables and API notes in this SKILL.md.
Show the pre-submit parameter table including the full expanded prompt; wait for confirm or edits.
After confirmation, run node {baseDir}/scripts/video_gen.js wait --json '...' with the expanded prompt.
Parse stdout JSON and return video URLs; on failure, surface errorCode / errorMessage and suggest parameter fixes.

CLI reference

node {baseDir}/scripts/video_gen.js wait --json '{"model":"…","prompt":"…","duration":5,"aspect_ratio":"9:16"}'
node {baseDir}/scripts/video_gen.js wait --json '…' --dry-run
node {baseDir}/scripts/video_gen.js status --task-id <id>

Definition of done

Done when the user receives at least one playable video URL from the API response, or a clear failure explanation with next steps. All parameters used must fall within the selected model’s allowed sets in this document. The submitted prompt must be the expanded production prompt unless the user explicitly supplied a finished long prompt and asked not to rewrite it.

Boundaries (out of scope)

We do not review platform compliance, copyright, or likeness; we do not warrant commercial usability of outputs.
We do not provide offline rendering, traditional NLE projects, or API field combinations not documented here.
Do not hard-code absolute paths in this doc; {baseDir} is this skill root (next to SKILL.md).

Example prompts

Vertical clip: cutting thick glass, satisfying sound, crack spreading from one point
This image is a windowpane—animate a blade scratch and cracks growing in the reflection
Satisfying glass ASMR 9:16, clean slice, translucent look, not gory
Glass cutting ASMR 9:16, slow crack propagation, clean slice reveal

Default parameters

Field	Value
Model	KLING_V3_0_PRO
Aspect	9:16 (fixed, vertical short video)
Duration	5 s
Resolution	— (`KLING_V3_0_PRO` has no `resolution` field—do not send)
Audio	On (auto glass cut / shatter sounds)
Look	Extreme macro, cold white light, slow motion, minimal background, translucency first

API validity (default KLING_V3_0_PRO): Text-to-video: duration only 5 / 10 / 15, aspect_ratio only 9:16, 1:1, 16:9; image-to-video: aspect_ratio only 9:16, 16:9, 1:1; no resolution field—do not send. Fast VEO tier: text VEO_3_1_FAST, image CHATBOT_VEO_3_1_FAST, duration fixed 8, aspect_ratio only 9:16 or 16:9. For other model_key values, follow the allowed sets in this document; do not send unsupported fields.

Text-to-video: cutting glass

The user describes glass type and how it breaks; you generate the clip. Good for batch ideation and hook testing.

User should provide:

Glass type (clear / stained / tempered / frosted / laminated)
Cut or break style (straight score-and-snap / irregular cut / slow shatter / full burst / crack spread)
Optional: angle or detail (“shards fly”, “side light on refraction”)

Flow:

Collect glass type and break style; ask if missing.
Build an English prompt emphasizing cut marks, refraction, and break motion.

After confirmation, run ({baseDir} = this skill root):

node {baseDir}/scripts/video_gen.js wait --json '{"model":"KLING_V3_0_PRO","prompt":"(full English prompt)","aspect_ratio":"9:16","duration":5,"generate_audio":true}'

Match JSON to the confirmed table; add resolution only if the model supports it. Parse videos from stdout.

Return URLs and what to tweak next.

Parameters:

Field	Value
model	KLING_V3_0_PRO
aspect_ratio	9:16
duration	5
generate_audio	true

Sample prompt (stained glass straight cut):

Extreme close-up macro shot of vibrant stained glass being scored and snapped cleanly along a straight line, cold white backlighting makes colors saturate brilliantly, the crack propagates with satisfying precision, glass edge perfectly smooth, slow motion 240fps, dust motes caught in light beam, ASMR cutting sound, minimal white background, shallow depth of field

Sample prompt (tempered shatter):

Ultra close-up of tempered glass shattering into thousands of tiny cubed fragments in extreme slow motion, cold studio lighting catches every spinning shard, crystalline transparency, satisfying explosive burst contained in frame, glass pebbles cascade like water, cinematic depth of field, ASMR crunch and tinkle

Expected result: 5 s vertical clip with coherent cut/shatter motion, readable glass texture and light, synced break sounds, high completion rate.

Image-to-video: glass motion

User supplies a glass image URL; you add crack spread or cut motion on top of that look.

User should provide:

Image URL (public https only)
Desired motion (crack from center / blade scratch clean line / slow full break / edge chip)

Flow:

Validate https:// URL (not a local path).
Build motion prompt anchored to the image’s glass material.

After confirmation:

node {baseDir}/scripts/video_gen.js wait --json '{"model":"KLING_V3_0_PRO","prompt":"(full English prompt)","image":"(user HTTPS URL)","aspect_ratio":"9:16","duration":5,"generate_audio":true}'

Return URLs.

Parameters:

Field	Value
model	KLING_V3_0_PRO
aspect_ratio	9:16
duration	5
generate_audio	true
image	User’s image URL

Sample prompt (crack spread):

The glass surface in the image begins to crack, a single hairline fracture propagates outward in extreme slow motion, branching into a web of perfect cracks, cold white light refracts through each fracture line creating rainbow caustics, satisfying tension-release moment, ASMR glass stress sound

Expected result: Motion matches the uploaded glass; strong refraction; consistent with the source image.

Prompt building blocks

Brittle snap: satisfying snap, perfect clean break, zero resistance, ultra-brittle

Clean edge: laser-precise cut line, mirror-smooth edge, factory perfect, atomic-level clean slice

Clarity: crystal clear transparency, light refracts into spectrum, backlit caustics, liquid-like clarity

Safe tension: controlled shatter, contained explosion, safe distance macro, slow motion danger

Slow-mo: 240fps extreme slow motion, time dilation effect, every shard frozen mid-air

Note: Image URLs must be publicly reachable over HTTPS or the API will fail. Upload to a host first if needed.