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Agent Skill · 前端设计

kling-3-prompting(kling 3 提示)

用于辅助提示词、系统指令、Agent 行为约束和工作流模板的整理。它适合让 Agent 规范任务边界、统一输出格式、拆分操作步骤或优化提示词可复用性。使用时需要保留真实业务约束,不要把示例当硬规则;涉及自动执行、外部工具或高风险操作时,应在提示词中明确确认步骤、权限边界和失败处理方式。

kling-3-prompting 是前端设计类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为只读;许可证信息还不明确,第三方扫描已通过,按安装量在前端设计类的 10,216 个 Skill 里排第 1,282。

总安装 6,586周安装 280GitHub Stars 10下载 2,307核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:kling-3-prompting(kling 3 提示)
来源仓库:https://github.com/aedev-tools/kling-3-prompting-skill
仓库路径:skills/kling-3-prompting
安装命令:
npx skills add https://github.com/aedev-tools/kling-3-prompting-skill --skill kling-3-prompting
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/aedev-tools/kling-3-prompting-skill --skill kling-3-prompting

这个 Skill 是做什么的

前端设计类 Skill 关注页面结构、视觉规范和组件写法,输出通常是可运行的界面代码。

kling-3-prompting 辅助提示词、系统指令、Agent 行为约束和工作流模板的整理。适合让 Agent 规范任务边界、统一输出格式、拆分操作步骤或优化提示词可复用性。使用时需保留真实业务约束,不要把示例当硬规则;涉及自动执行时应明确确认步骤。

涉及外部工具或高风险操作时,应在提示词中明确权限边界和失败处理方式。该技能当前无额外说明,功能以实际实现为准。

来源仓库内路径:skills/kling-3-prompting

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/aedev-tools/kling-3-prompting-skill --skill kl…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

kling-3-prompting 怎么安装?

在终端执行 npx skills add https://github.com/aedev-tools/kling-3-prompting-skill --skill kling-3-prom…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

kling-3-prompting 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

kling-3-prompting 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

kling-3-prompting 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

kling-3-prompting 用的人多吗?

公开数据是累计安装 6,586 次,近一周安装 280 次,下载 2,307 次,GitHub 10 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

kling-3-prompting 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理前端设计类任务、又不想每次都手写提示词的人。
  • 只想先试试效果、不希望它改动本地文件的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

前端设计类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
frontend-design

前端设计 · Codex、Claude

8,823,360126,072只读MIT通过
vercel-composition-patterns

Vercel 组合模式 · Codex、Claude

3,858,81625,893需要联网MIT通过
vercel-react-native-skills

Vercel React native skills 前端 · Codex、Claude

2,468,66425,878只读MIT通过
adapt

adapt 搜索 · Codex、Claude

2,027,04023,125操作浏览器未明确通过
bolder

bolder 分析 · Codex、Claude

2,004,28823,130只读未明确通过
kling-3-prompting

kling 3 提示 · 本页

6,58610只读未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Overview

Kling 3.0 is a unified multimodal video model. It understands cinematic direction, not keyword lists. Write prompts like a director — describe what the audience sees, hears, and feels over time.

Core shift: Description → Direction. Think "direct a scene" not "describe an image."

Interactive Builder Workflow

When invoked, guide the user through these steps using AskUserQuestion:

digraph builder {
  "1. Generation mode?" [shape=diamond];
  "Text-to-Video" [shape=box];
  "Image-to-Video" [shape=box];
  "Multi-Shot Sequence" [shape=box];
  "Keyframe Transition" [shape=box];
  "2. Gather scene details" [shape=box];
  "3. Assemble prompt" [shape=box];
  "4. Present & refine" [shape=box];

  "1. Generation mode?" -> "Text-to-Video";
  "1. Generation mode?" -> "Image-to-Video";
  "1. Generation mode?" -> "Multi-Shot Sequence";
  "1. Generation mode?" -> "Keyframe Transition";
  "Text-to-Video" -> "2. Gather scene details";
  "Image-to-Video" -> "2. Gather scene details";
  "Multi-Shot Sequence" -> "2. Gather scene details";
  "Keyframe Transition" -> "2. Gather scene details";
  "2. Gather scene details" -> "3. Assemble prompt";
  "3. Assemble prompt" -> "4. Present & refine";
}

Step 1: Determine Generation Mode

Ask the user which mode:

  • Text-to-Video — prompt from scratch
  • Image-to-Video — animate a reference image
  • Multi-Shot Sequence — 2-6 shot storyboard (up to 15s)
  • Keyframe Transition — start frame → end frame with interpolated motion

Step 2: Gather Scene Details

Ask about each element (adapt questions to mode):

ElementQuestionWhy it matters
SubjectWho/what is the focus? Specific appearance details?Anchors consistency — define distinguishing traits early
ActionWhat happens? Describe the timeline (first → then → finally)Kling 3.0 excels at sequential action over 15s arcs
EnvironmentWhere? Be specific (not "a street" but "narrow Tokyo alley, steam from grates")Grounds the scene physically
CameraShot type and movement? (See camera reference below)Cinematic language produces far better results
LightingWhat light sources? Name them specifically"Flickering neon" beats "dramatic lighting"
Mood/EmotionWhat should the audience feel?Drives color grade, pacing, music
AudioDialogue? Ambient sound? Music?Kling 3.0 generates native audio + lip-sync
DurationHow long? (3-15s)Longer = describe progression over time
Aspect Ratio16:9 / 9:16 / 1:1 / 21:9?16:9 cinematic, 9:16 social, 21:9 ultra-wide

Image-to-Video: Focus on how the scene *evolves from* the image — movement, camera motion, environmental change. The model preserves identity/layout from the source.

Keyframes: Ask for start and end frame descriptions. Frames should match in color, style, and lighting. Prompt sparingly — Kling infers motion well.

Multi-Shot: Define each shot separately with its own framing, subject, action, and duration. Label shots explicitly.

Step 3: Assemble the Prompt

Use the Master Formula:

[Scene/Environment] + [Subject & Appearance] + [Action Timeline] + [Camera Movement] + [Audio & Atmosphere] + [Technical Specs]

Writing rules:

  • Use cinematic motion verbs: dolly push, whip-pan, crash zoom, rack focus, tracking shot — NOT "moves" or "goes"
  • Name real light sources: neon signs, candlelight, golden hour, LED panels — NOT "dramatic lighting"
  • Include texture for credibility: grain, lens flares, condensation, fabric sheen, smoke, sweat
  • Describe temporal flow: beginning → middle → end
  • Keep to 1-3 rich sentences per shot (specificity > length)
  • For dialogue: use character labels, assign voice tone/emotion, use transitional words ("Immediately," "Pause")

Step 4: Present & Refine

Present the assembled prompt. Ask if they want to:

  • Adjust any element
  • Add a negative prompt
  • Generate variations (different duration, different camera, different mood)

Quick Reference

Camera Movements

MovementEffectExample phrase
Dolly push-inBuilds intimacy/tension"slow dolly push-in toward her face"
Dolly zoomVertigo/dramatic reveal"dolly zoom creating disorienting depth shift"
Tracking shotFollows subject laterally"camera tracks alongside as she walks"
Whip-panEnergy/surprise"whip-pan to reveal the door"
Crash zoomShock/emphasis"sudden crash zoom on the object"
Rack focusShift attention"rack focus from foreground hand to background figure"
Handheld/shoulder-camRaw/documentary feel"handheld shoulder-cam with subtle sway"
Static tripodComposed/observational"locked-off static tripod, wide shot"
FPV droneHigh-energy immersion"dynamic FPV drone shot chasing through corridor"
Low-angle trackingHeroic/imposing"low-angle tracking shot, subject towers above"
Truck left/rightLateral reveal"camera trucks right revealing the cityscape"
Tilt up/downVertical reveal"slow tilt up from boots to face"

Lens & Film Stock

PhraseEffect
"Shot on 35mm film"Warm grain, organic texture
"Macro 85mm lens"Tight detail, shallow depth of field
"Wide-angle steadicam"Smooth, immersive, spatial
"Handheld camcorder"Raw VHS energy, nostalgic
"Anamorphic lens flare"Cinematic horizontal streaks

Lighting

Use specific sources, not adjectives:

  • "Golden hour sun cutting through dusty warehouse windows"
  • "Flickering neon casting magenta/cyan across wet pavement"
  • "Single bare bulb swinging, casting moving shadows"
  • "Cool blue LED panels reflecting off glass surfaces"
  • "Candlelight warming skin tones, deep shadows beyond"

Color & Grade

  • "Desaturated teal grade, crushed blacks"
  • "Amber nightclub strobe cutting through smoke"
  • "Cool blue haze filling the corridor"
  • "Magenta neon reflecting off wet asphalt"
  • "Overexposed highlights, blown-out whites"

Multi-Character Dialogue

RuleDoDon't
Name characters[Character A: Silver-haired CEO][Man] says...
Anchor to action*Agent slams table.* [Agent, angrily]: "Where is it?"Just dialogue without visual action
Assign voice tone[CEO, deep authoritative gravelly voice]Generic "says"
Control timing"Immediately," "Pause," "After a beat"Back-to-back dialogue without transitions

Multi-Shot Structure

Shot 1 (0-5s): [Wide establishing shot description]
Shot 2 (5-10s): [Medium/close-up with action progression]
Shot 3 (10-15s): [Resolution/reaction with camera payoff]

Atmosphere: [Overall mood, color grade]
Audio: [Sound design, music, dialogue]

Label every shot. Assign durations. Describe framing + subject + motion per shot.

Start & End Frame Tips

  • Frames should match in color palette, style, and lighting
  • Identical start/end frames = seamless loop
  • Prompt sparingly — Kling infers motion between frames well
  • Simple camera directions: zoom in/out, pan left/right, tilt up/down
  • 5s for dynamic transitions, 10s for complex transformations
  • Start frame aspect ratio drives the whole clip

Negative Prompts

Use to prevent common AI defaults:

smiling, laughing, cartoonish, bright saturated colors, low resolution,
morphing, blurry text, disfigured hands, extra fingers, static pose,
frozen expression, stock photo aesthetic

Customize based on scene — remove items that conflict with your intent.

Weak → Strong

ElementWeakStrong
Camera"Camera follows person""Handheld shoulder-cam drifts behind subject with subtle sway"
Subject"A woman walking""Woman in red dress, heels clicking wet cobblestone"
Environment"In a city""Narrow Tokyo alley, steam from grates, glowing vending machines"
Lighting"Dramatic lighting""Flickering neon casting magenta/cyan across wet pavement"
Texture"It looks realistic""Rain beading on leather jacket, condensation on glass, visible breath"
Motion"She walks away""She turns slowly, hair catches light, disappears around corner"

Common Mistakes

MistakeFix
Keyword lists instead of scene directionWrite like directing a shot: subject + action + camera + environment
Vague motion ("moves," "goes")Use cinematic verbs: dolly, track, whip-pan, crash zoom
Generic lighting ("dramatic")Name the source: neon, candle, golden hour, LED panel
Overlong prompts1-3 rich sentences per shot; specificity > length
No temporal progressionDescribe beginning → middle → end of the shot
Mismatched keyframesMatch color, lighting, and style between start/end frames
Unattributed dialogueLabel every speaker with name, tone, and emotion
Cramming multi-shot into one paragraphSeparate and label each shot with duration

平台分布

Codex

39.42%
按下载量换算909

Claude

28.27%
按下载量换算652

Cursor

19.8%
按下载量换算457

Gemini CLI

10.39%
按下载量换算240

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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