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Carpet Wash Video

面向清洁/满意感短视频创作者:依据地毯类型与污渍描述,或脏地毯的 https 图片,先把简短需求扩展成完整英文分镜提示词,经用户确认后调用 WeryAI 生成 9:16 竖屏清洗视频,默认 KLING 模型、5 秒、含 ASMR 音频,返回可播放链接。

zoucdr
zoucdr
热度 38.11
最近更新 2026-05-11 17:34:40
分类:创作依赖:代码执行 / 第三方 API应用场景:视频编辑 / 社交媒体

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add carpet-wash-video
Metadata
name
carpet-wash-video
version
1.0.0
description
Generate satisfying vertical carpet deep-clean shorts (WeryAI): text-to-video or dirty rug photo to rinse, grime runoff, and fiber revival. Use when you need carpet cleaning satisfying video, stain removal rinse, dirty-to-clean reveal, or users ask for grime line, fluffy pile comeback, before/after contrast.
tags
["cleaning","satisfying","asmr","short-video","vertical"]
metadata
{"openclaw":{"emoji":"🧹","primaryEnv":"WERYAI_API_KEY","paid":true,"network_required":true,"requires":{"env":["WERYAI_API_KEY"],"bins":["node"],"node":">=18"}}}
user-invocable
true

Carpet wash & restore videos

For cleaning / satisfying creators: pressure rinse, brush agitation, dirty water running out, fibers standing up again—strong before/after and ASMR wash sounds. One prompt or one dirty carpet photo.

Dependencies: scripts/video_gen.js + WERYAI_API_KEY + Node.js 18+.

Prerequisites

  • WERYAI_API_KEY must be set.
  • Node.js 18+; images must be https URLs.

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).
  • Optional URL overrides (WERYAI_BASE_URL, WERYAI_MODELS_BASE_URL): video_gen.js defaults to https://api.weryai.com and https://api-growth-agent.weryai.com. Overrides are intended for testing or approved alternate endpoints. If these variables are set in your environment, confirm they point to hosts you trust—otherwise prompts, images, and your bearer token could be sent elsewhere.
  • 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

  • Wash physics: water/foam migration, dirty runoff, fiber lift, before/after color stripe or patch.
  • Camera: top-down or low side angle; slow motion on squeeze or extractor pass; ASMR-forward if audio on.
  • Stains: tie language to user rug type (mud, pet, grey traffic) and method (pressure, brush, steam).

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

Workflow

  1. Confirm scenario (text-to-video and/or image-to-video as documented).
  2. Collect the user's brief, optional https image URL, tier (best / good / fast) or explicit model.
  3. Expand prompt (mandatory): Unless the user supplied a finished long prompt and asked not to rewrite, expand the brief with full shot, light, wash physics, and audio cues per ## Prompt expansion (mandatory). Do not submit a one-liner.
  4. Check the expanded prompt against prompt_length_limit if listed for the model; trim if needed.
  5. Verify duration, aspect_ratio, generate_audio, and other fields against this doc.
  6. Show the confirmation table with the full expanded prompt; wait for confirm or edits.
  7. After confirmation, run node {baseDir}/scripts/video_gen.js wait --json '...' with the expanded prompt.
  8. Return playable URL(s) or clear error guidance.

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

Playable URL(s) or clear failure; parameters within model limits. 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)

  • No legal/commercial guarantees; no offline editing stacks; {baseDir} only—no absolute paths.

Example prompts

  • Filthy living-room rug, pressure washer leaves a clean stripe, vertical satisfying
  • From this moldy carpet photo—rinse and dark water pouring off
  • OCD clean macro: pile goes grey to bright, foam and squeeze moment
  • Satisfying carpet deep clean 9:16, dirty-to-clean reveal line

Default parameters

Field Value
Model KLING_V3_0_PRO
Aspect 9:16
Duration 5 (short hook)
Audio On (brush, water, squeeze ASMR)
Look Top-down close, soft light, extreme before/after color, slow grime flow, minimal background

API validity (KLING_V3_0_PRO): Text: duration 5 / 10 / 15, aspect_ratio 9:16, 1:1, 16:9; image: aspect_ratio 9:16, 16:9, 1:1; no resolution. VEO fast: VEO_3_1_FAST / CHATBOT_VEO_3_1_FAST, duration 8, aspect_ratio 9:16 or 16:9. Other keys: follow tables here.


Text-to-video: wash process

User provides: rug type (short pile / shag / weave / vintage / pet mat), stain type (overall grey / embedded fur / mud spot / drink / years of dust), optional method (pressure / brush / steam / extractor).

Flow: collect → build English prompt (runoff, color return, fiber lift) → run:

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

Parameters: model KLING_V3_0_PRO, 9:16, 5, generate_audio true.

Expanded prompt: Build per ## Prompt expansion (mandatory) from the user's rug/stain brief; do not paste fixed samples.

Expected: Visible dirty water, strong color bounce-back, ASMR-friendly audio.


Image-to-video: clean the photo rug

User provides: https image URL + effect (pressure / brush / extract / steam).

Flow: validate URL → prompt matched to stains in image →

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

Expected: Grime matches photo; true color emerges; pattern continuity.


Prompt blocks

Grime: thick dark water flows outward, murky brown runoff cascades, grime releases in satisfying rivulets

Color return: vivid original color emerges beneath, saturated hues pop, before-after color contrast in single frame

Pile: fibers lift and separate, pile stands upright after cleaning, fluffy texture restored

Sound: ASMR scrubbing, pressure washer hiss, wet squeegee drag

Upload local shots to a public host first; API needs reachable HTTPS.