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Agent Skill · 开发

lovstudio%3axbti-creator(lovstudio%3axbti 创建者)

lovstudio%3axbti-creator 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

lovstudio%3axbti-creator 是开发类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为接触敏感数据;许可证信息还不明确,暂无第三方扫描结果,按安装量在开发类的 21,746 个 Skill 里排第 13,944。

总安装 784周安装 33GitHub Stars 45下载 275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:lovstudio%3axbti-creator(lovstudio%3axbti 创建者)
来源仓库:https://github.com/lovstudio/skills
仓库路径:skills/lovstudio%3Axbti-creator
安装命令:
npx skills add https://github.com/lovstudio/skills --skill lovstudio:xbti-creator
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/lovstudio/skills --skill lovstudio:xbti-creator

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

lovstudio%3axbti-creator 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息。适合在 Codex、Claude、Cursor、Gemini CLI 中围绕仓库状态、代码变更或协作事项进行整理。

通过 npx skills add 命令从指定 GitHub 仓库安装并使用该技能。安装前需确认权限范围和维护状态,注意可能触发联网、命令执行或文件读写操作。建议结合原始 README 和仓库内容进一步核验具体功能和用法边界。

来源仓库内路径:skills/lovstudio%3Axbti-creator

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/lovstudio/skills --skill lovstudio:xbti-creato…;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

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

lovstudio%3axbti-creator 怎么安装?

在终端执行 npx skills add https://github.com/lovstudio/skills --skill lovstudio:xbti-creator。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

lovstudio%3axbti-creator 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。

lovstudio%3axbti-creator 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

lovstudio%3axbti-creator 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。

lovstudio%3axbti-creator 用的人多吗?

公开数据是累计安装 784 次,近一周安装 33 次,下载 275 次,GitHub 45 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。

lovstudio%3axbti-creator 安全吗?

没有查到第三方扫描结果,安全性无法从公开资料判断,安装前请自行审查源码、依赖和命令行为。

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。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 没有第三方扫描结果,安全性只能靠自己读源码判断。
  • 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。
  • 需要处理开发类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要明确授权才能用到公司项目里的场景。
  • 要求有安全扫描结论才肯安装的团队。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
lovstudio%3axbti-creator

lovstudio%3axbti 创建者 · 本页

78445接触敏感数据未明确未收录

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

xbti-creator — Create Your Own BTI Personality Test

Generate a complete, deployable BTI personality test website from a theme and preferences. Based on the proven XBTI architecture (React + Vite), with AI-generated content.

When to Use

  • User wants to create a themed personality test (e.g., LBTI for lobsters, FBTI for founders)
  • User says "创建一个XX人格测试" or "make a custom BTI"

Workflow (MANDATORY)

Step 1: Collect Theme Info

Use AskUserQuestion to gather:

FieldExampleRequired
BTI名称LBTIYes
主题龙虾的人格分析Yes
风格偏好幽默毒舌 / 温暖治愈 / 学术严肃Yes
人格数量16-25(默认20)No
特殊彩蛋人格有/无(默认有)No
项目目录默认 ~/projects/{NAME}No
提交到 Gallery是/否(默认否)— 提交到 xbti.lovstudio.ai 供他人体验No

Step 2: Environment Setup

After collecting user input, silently check and auto-fix the environment:

# 1. Node.js (required)
node --version  # Need 18+

# 2. Detect package manager
command -v pnpm && echo "USE_PM=pnpm" || command -v bun && echo "USE_PM=bun" || echo "USE_PM=npm"

# 3. git
git --version

# 4. image-creator skill
ls ~/.claude/skills/lovstudio-image-creator/gen_image.py 2>/dev/null && echo "OK" || echo "MISSING"

# 5. Zenmux API key
[ -n "$ZENMUX_API_KEY" ] && echo "OK" || echo "MISSING"

# 6. Python deps
python3 -c "import google.genai; from PIL import Image" 2>/dev/null && echo "OK" || echo "MISSING"

Auto-fix (no user interaction needed for these):

  • lovstudio:image-creator missing → npx skills add lovstudio/skills --skill lovstudio:image-creator
  • Python deps missing → pip install google-genai Pillow --break-system-packages 2>/dev/null || pip3 install google-genai Pillow

Require user input only if truly blocked:

  • Node.js missing → tell user to install and stop
  • ZENMUX_API_KEY missing → ask user to provide it:

1. 注册 Zenmux: https://zenmux.ai/invite/K6KT2X (邀请码,有免费额度) 2. 获取 API Key: https://zenmux.ai/settings/keys 3. 设置: export ZENMUX_API_KEY="your-key" (建议加到 ~/.zshrc)

Do NOT proceed to Step 3 until environment is fully ready.

Step 3: Design Dimension System

Based on the theme, design 5 维度模型, each with 3 子维度 = 15 dimensions total.

Rules:

  • Dimension names must be thematic (e.g., for lobster BTI: "钳力模型", "深海适应模型")
  • Each sub-dimension measures a distinct aspect on a L/M/H scale
  • Keep dimension IDs short: D1-D15 or thematic prefixes (C1, C2, C3, S1, S2, S3...)
  • Write L/M/H explanations for each dimension (one-line, matching the BTI's tone)

Output: src/data/dimensions.js — see references/xbti-data-format.md for exact format.

Step 4: Generate Questions

Generate 30 questions (2 per dimension), each with 3 options (value 1, 2, 3).

Rules:

  • Questions must match the theme and tone
  • Option values: 1 = low on that dimension, 2 = medium, 3 = high
  • Mix question styles: direct statements, scenarios, hypotheticals
  • Include 1-2 memorable/funny questions per model for engagement
  • Optionally: add 1-2 special trigger questions for a hidden personality type

Output: src/data/questions.js

Step 5: Design Personality Types

Generate 16-25 personality types, each with:

FieldDescription
code4-6 char English code (creative, memorable)
cn2-3 char Chinese name
pattern15-char L/M/H pattern matching the dimension system
introOne-line tagline (catchy, in-character)
desc200-400 char personality description (match chosen tone)

Rules:

  • Codes should be thematic and creative (not generic like TYPE-A)
  • Patterns must cover the L/M/H space well — avoid clustering
  • Include 1 fallback type (for < 60% match) and optionally 1 hidden type
  • Descriptions should be entertaining and shareable — this is what goes viral

Output: src/data/types.js

Step 6: Scaffold the Project

Clone the XBTI template from GitHub and clean up:

git clone https://github.com/lovstudio/XBTI.git {TARGET_DIR}
cd {TARGET_DIR}

# Remove origin-specific files, keep the engine
rm -rf .git .vercel image/* CHANGELOG.md docs/
mkdir -p image
git init

# Fix packageManager field for user's environment
# If user uses npm: remove the packageManager field entirely
# If user uses bun: change to bun
# If user uses pnpm: keep as-is

packageManager handling (important for portability):

  • The cloned package.json has "packageManager": "pnpm@x.y.z"
  • If user doesn't use pnpm, remove this field to avoid errors
  • Then run {PM} install with whatever package manager the user has

Then overwrite the data files with generated content:

  • src/data/dimensions.js
  • src/data/questions.js
  • src/data/types.js

Update branding in:

  • index.html — title, meta tags
  • src/components/IntroScreen.jsx — hero title, subtitle, attribution
  • src/index.css — theme colors (optional, ask user)
  • package.json — name, description, remove packageManager if needed

Keep src/logic/scoring.js as-is — the algorithm is universal. Only update import paths if dimension IDs changed.

Step 7: Generate Avatar Images

For each personality type, programmatically generate an avatar image using the lovstudio:image-creator skill.

Prompt Crafting (nano-banana-pro style):

For each personality type, craft a prompt optimized for stylized character generation:

[Subject: character visual based on personality], [Action/Pose],
[Environment: thematic background], chibi style character,
cute cartoon illustration, simple flat design, vibrant colors,
white background, centered composition,
best quality, masterpiece, ultra high res, 8k

Examples:

  • CTRL (控制者): "A confident chibi character with arms crossed, wearing a golden crown, standing on a glowing control panel with buttons and levers, chibi style, cute cartoon illustration, simple flat design, vibrant colors, white background, centered composition, best quality, masterpiece, 8k"
  • DEAD (死者): "A peaceful chibi ghost character floating with closed eyes, translucent body, surrounded by ZZZ symbols and stars, chibi style, cute cartoon illustration, simple flat design, soft muted colors, white background, centered composition, best quality, masterpiece, 8k"

Generation Process:

  1. Craft all prompts (one per personality type), present to user
  2. Ask user: "先生成一个预览确认风格,还是直接批量生成全部?"
  3. Preview mode: Generate one image, show result, iterate on prompt style if needed: python3 ~/.claude/skills/lovstudio-image-creator/gen_image.py \ "PROMPT_HERE" \ -o {TARGET_DIR}/image/{CODE}.png \ -q medium --no-open
  4. Batch mode: Once style confirmed, loop through all types: # For each personality type: python3 ~/.claude/skills/lovstudio-image-creator/gen_image.py \ "PROMPT_FOR_TYPE" \ -o {TARGET_DIR}/image/{CODE}.png \ -q medium --no-open Use Read tool to display each generated image to user for quick review.
  5. Verify all images exist: ls -la {TARGET_DIR}/image/

IMPORTANT: All image generation is fully automated via CLI — do NOT ask user to manually download or operate any web UI.

Step 8: Install & Launch

cd {TARGET_DIR}

# Install dependencies with user's package manager
{PM} install

# Start dev server
{PM} run dev
# or: npx vite (universal fallback)

Tell the user the dev server URL (usually http://localhost:5173) and invite them to test the full flow.

Step 9: Submit to XBTI Gallery (Optional)

Skip this step if user chose NOT to submit in Step 1.

If user chose to submit, create a PR to lovstudio/XBTI repo:

# 1. Fork & clone the XBTI repo
cd /tmp
gh repo fork lovstudio/XBTI --clone
cd XBTI

# 2. Create case directory (follow existing structure: cases/sbti/, cases/cbti/)
CASE_NAME=$(echo "{BTI_NAME}" | tr '[:upper:]' '[:lower:]')
mkdir -p cases/${CASE_NAME}/images

# 3. Copy data files + images
cp {TARGET_DIR}/src/data/dimensions.js cases/${CASE_NAME}/
cp {TARGET_DIR}/src/data/questions.js cases/${CASE_NAME}/
cp {TARGET_DIR}/src/data/types.js cases/${CASE_NAME}/
cp {TARGET_DIR}/image/*.png cases/${CASE_NAME}/images/

# 4. Create index.js (re-export entry point, required by registry)
cat > cases/${CASE_NAME}/index.js << EOF
export const meta = { id: '${CASE_NAME}', name: '${BTI_NAME}', desc: '${THEME}', author: '$(git config user.name)', authorUrl: '' };
export { dimensionMeta, dimensionOrder, DIM_EXPLANATIONS } from './dimensions.js';
export { questions } from './questions.js';
export { TYPE_LIBRARY, TYPE_IMAGES, NORMAL_TYPES } from './types.js';
EOF

# 5. Create case.json (combined metadata + data for static access)
#    Use Node.js to merge all data into a single JSON file:
node -e "
const dim = require('./cases/${CASE_NAME}/dimensions.js');
const q = require('./cases/${CASE_NAME}/questions.js');
const t = require('./cases/${CASE_NAME}/types.js');
const data = {
  meta: { id: '${CASE_NAME}', name: '${BTI_NAME}', desc: '${THEME}', author: '$(git config user.name)', authorUrl: '' },
  ...dim, ...q, ...t
};
require('fs').writeFileSync('./cases/${CASE_NAME}/case.json', JSON.stringify(data, null, 2));
"

# 6. Update cases/registry.js — add import and entry
#    Read current registry, add new import and array entry
# 7. Update cases/index.json — add new case metadata entry

# 8. Create PR
git checkout -b add-case/${CASE_NAME}
git add cases/${CASE_NAME} cases/registry.js cases/index.json
git commit -m "feat: add ${BTI_NAME} case (${THEME})"
git push origin add-case/${CASE_NAME}
gh pr create \
  --repo lovstudio/XBTI \
  --title "feat: add ${BTI_NAME} (${THEME})" \
  --body "$(cat <<'PREOF'
## New BTI Case

- **Name**: {BTI_NAME}
- **Theme**: {THEME}
- **Style**: {STYLE}
- **Types**: {TYPE_COUNT} personality types

Generated with [xbti-creator](https://github.com/lovstudio/skills)
PREOF
)"

Update cases/registry.js: Add import * as {CASE_NAME} from './{CASE_NAME}'; and append to the CASES array.

Update cases/index.json: Append {"id":"{CASE_NAME}","name":"{BTI_NAME}","desc":"{THEME}","author":"...","authorUrl":"..."} to the array.

Tell user the PR URL and that it will appear on xbti.lovstudio.ai after merge.

# Clean up
rm -rf /tmp/XBTI

Reference Files

  • references/xbti-data-format.md — exact data structure format for all files

Design Principles

  1. Theme consistency — every element (dimensions, questions, types, avatars) must feel thematic
  2. Shareability — personality descriptions should be entertaining enough to screenshot and share
  3. Balance — personality types should cover the spectrum, no type should feel "objectively better"
  4. Humor — even serious themes benefit from wit in the descriptions
  5. Completeness — the output should be a fully working, deployable website

平台分布

Codex

34.28%
按下载量换算94

Claude

29.5%
按下载量换算81

Cursor

18.1%
按下载量换算50

Gemini CLI

9.49%
按下载量换算26

安全审计

暂无安全审计结果可展示。

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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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