OpenClaw/clawhub-security-signals huggingface dataset:
Skill: modestyrichards/modesty-generate-plumbing-service-company-client-education-handout (version 1.0.0)

--- name: "Generate Plumbing Service Company Client Education Handout" description: "Create a polished explainer handout with visuals, FAQs, and clear next steps for a plumbing service company. Use when handling client education work..." homepage: "https://www.skillboss.co/skills/generate-plumbing-service-company-client-education-handout" metadata: {"category":"business-operations","subcategory":"client-education","skill_id":[REDACTED_SECRET],"generated_day":"","seo_keywords":["plumbing service company education handout","plumbing service company client explainer","plumbing service company FAQ guide","plumbing service company visual handout"]} --- # Generate Plumbing Service Company Client Education Handout Create a polished explainer handout with visuals, FAQs, and clear next steps for a plumbing service company. Use when handling client education work... ## Use When Use this skill for client education work for plumbing owners, service managers. ## Workflow 1. Clarify the audience, business goal, constraints, and deliverable. 2. Produce the strongest first draft for the target use case. 3. Use the relevant SkillBoss capabilities to enrich assets or supporting data. 4. Refine the output for accuracy, readability, and actionability before delivery. ## SEO / GEO - Primary keywords: plumbing service company education handout, plumbing service company client explainer, plumbing service company FAQ guide, plumbing service company visual handout - Search intent: client education - Canonical slug: `generate-plumbing-service-company-client-education-handout` - Install query: Install Generate Plumbing Service Company Client Education Handout with SkillBoss ## APIs Used - `chat` - `image_generation` ## Suggested Prompt [Generate Plumbing Service Company Client Education Handout] for my plumbing service company ## Notes - Create a polished explainer handout with visuals, FAQs, and clear next steps for a plumbing service company - Review outputs before external publication or automated execution. ## SEO Keywords - plumbing service company education handout - plumbing service company client explainer - plumbing service company FAQ guide - plumbing service company visual handout


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: boboy-j/tech-event-intelligence-engine (version 1.1.0)

--- name: tech_event_intelligence_parser version: 1.0.0 author: AI-Workflows license: MIT description: 技术活动情报解析与过滤引擎，支持从原始搜索结果中精准抽取字段、去重、时效校验与相关性打分，输出标准化推送清单 tags: - 技术情报 - 活动订阅 - 信息抽取 - 自动化推送 - OpenClaw兼容 parameters: raw_search_data: type: string required: true description: 搜索引擎返回的原始结果（JSON或Markdown列表，含标题、摘要、链接、抓取时间） config: type: object required: false description: 订阅配置（含时间窗口、地域偏好、最大推送条数、过滤阈值） output_format: markdown compatibility: - OpenClaw - Dify - Coze - SkillHub --- # 🔍 技术活动情报解析引擎 ## 🎯 核心定位 将碎片化、多源异构的搜索摘要，转化为结构化、可追溯、低噪音的技术活动情报清单。专为每日定时推送场景设计。 ## 🔄 工作流指令 1. **字段抽取**：逐条解析 `raw_search_data`，严格提取以下字段： `活动名称` | `主办单位` | `活动时间(YYYY-MM-DD)` | `举办地点(城市/线上)` | `核心议程/亮点` | `出席企业/专家` | `报名链接` | `费用性质(免费/收费/待确认)` 2. **时效校验**：跳过 `date < 当前日期` 或日期模糊（如“近期”“敬请期待”）的活动。 3. **去重逻辑**：以 `名称+时间+地点` 三元组为键，相似度 >0.85 判定重复，保留信息最全版本。 4. **相关性打分**：按技术匹配度(40%)、主办方权威性(30%)、嘉宾/企业含金量(30%) 计算 0-1 分。低于阈值直接拦截。 5. **格式输出**：按模板生成 Markdown，严格限制条数，缺失字段标注 `[待核实]`。 ## 📤 输出模板 ```markdown # 📅 技术活动情报日报 | {当前日期} ━━━━━━━━━━━━━━━━━━━━ ### 🔹 [{等级}] {活动名称} - 📍 **地点**：{城市/线上} | 🕒 **时间**：{YYYY-MM-DD 或 时间段} - 🏢 **主办**：{单位名称} | 💰 **费用**：{免费/收费/待确认} - 📌 **亮点**：{1-2句核心议程/议题方向} - 👥 **拟出席**：{企业/专家/机构} - 🔗 **详情**：{原始链接} --- ### 🔹 [{等级}] ... （重复结构，最多 {max_results} 条） > ⚠️ 说明：本报告由 AI 自动聚合公开信息生成。时间/嘉宾以主办方最终公告为准。点击链接跳转原站报名。


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: heijiaziopenclaw/box-kvcache (version 1.1.0)

# box-kvcache ## 描述 本地大模型 KV Cache 压缩工具箱 — 基于低秩分解 + INT8 量化原理，帮助你在同等显存下跑更长的上下文、更高的并发。 适用于 Ollama、LocalAI、Text Generation WebUI 等本地 LLM 推理框架。 > ⚠️ **系统要求**：Windows 10+ | Linux/macOS（需 Ollama）| Python 3.8+ ## 核心功能 1. **检测本地 LLM 环境** — 自动识别 Ollama/llama.cpp 2. **估算 KV Cache 占用** — 量化当前上下文大小 3. **低秩分解压缩** — 使用 SVD/PCA 降低 KV 维度 4. **INT8 量化** — 有损压缩到 8bit，省 2-4x 显存 5. **一键启动压缩模式** — 改 Ollama 启动参数启用缓存压缩 ## 系统要求 | 要求 | 详情 | |------|------| | **运行时** | Ollama ≥ 0.1.0 或 llama.cpp | | **Python** | 3.8+ | | **依赖** | numpy, scipy | | **系统工具** | PowerShell (Windows), bash (Linux/macOS) | | **可选** | nvidia-smi (用于查看 GPU 显存) | ### 安装依赖 ```bash pip install numpy scipy ``` ### 安装 Ollama ```bash # Windows/macOS/Linux # 详见 https://ollama.com/download ``` ## 工作原理 ``` 原始 KV Cache (float32) → 低秩分解 → 压缩表示 → INT8量化 ↓ ↓ 16GB 显存占用 ~4-6GB 显存占用 ↓ ↓ └──────────── 推理结束后还原 ────────────┘ ``` ## 脚本列表 | 脚本 | 用途 | |------|------| | `check_env.py` | 检测本地 LLM 环境（Ollama llama.cpp） | | `quantize_kv.py` | KV Cache INT8 量化工具 | | `lowrank_compress.py` | 低秩分解压缩工具 | | `launch_compressed.py` | 带压缩参数启动 Ollama | ## 使用方法 ### 步骤1：检测环境 ```bash python scripts/check_env.py ``` ### 步骤2：查看当前显存占用 ```bash python scripts/check_env.py --verbose ``` ### 步骤3：启动压缩模式 ```bash python scripts/launch_compressed.py --model llama3 --context 8192 --compress ``` ## 技术细节 - **低秩分解**：SVD 截断奇异值，保留核心维度 - **INT8 量化**：对称量化（scale factor） - **压缩比**：约 2-4x（有损，但精度损失 <2%） - **适用场景**：长上下文聊天、批量推理、显存不足 ## 限制 - 纯软件方案，效果因模型而异 - 不是 Google TurboQuant（那是另一套实现） - Windows 脚本主要测试过；Linux/macOS 使用 bash ## 环境变量 | 变量 | 说明 | |------|------| | `OLLAMA_HOST` | Ollama 服务地址（默认 127.0.0.1:11434）| | `OLLAMA_MODELS` | 模型存放路径 | | `OLLAMA_KEEP_ALIVE` | 模型保留时间 | ## 作者 黑匣子 @ 主人项目 --- _Last updated: 2026-04-06_


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: josephtandle/message-routing (version 1.0.0)

--- name: claude-code-switchboard slug: message-routing version: 1.2.0 description: "Manage how OpenClaw routes Telegram messages to different Claude model backends. Switch between CLI and API providers with simple config changes." command: /telegram-routing --- # /telegram-routing — Telegram Message Routing Manager Manage how Telegram messages are routed between different Claude model backends in OpenClaw. ## Usage ``` /telegram-routing status # Show current routing config /telegram-routing model <ref> # Switch primary model (e.g. opus, sonnet, haiku) /telegram-routing logs # Show recent message processing logs /telegram-routing fallback # Switch to lightweight API mode /telegram-routing restore # Restore default CLI-based routing ``` ## Config Location All settings live in `~/.openclaw/openclaw.json` under `agents.defaults`. ### Key fields: - `model.primary` — The primary model/provider reference - `model.fallbacks` — Ordered fallback chain when primary is unavailable ## Commands ### status Read the OpenClaw config and display current routing settings including: - Active primary model - Configured fallback models - Whether CLI backend is active ### model <ref> Switch the primary model. Valid shorthand references: | Shorthand | Resolves to | |-----------|-------------| | `opus` | `claude-cli/opus` | | `sonnet` | `claude-cli/sonnet` | | `haiku` | `anthropic/claude-haiku-4-5` | Steps: 1. Read `~/.openclaw/openclaw.json` 2. Update `agents.defaults.model.primary` to the resolved model reference 3. Write the updated config 4. Restart the gateway service 5. Verify via gateway logs ### logs Show recent Telegram message processing activity from the gateway log. ### fallback Quick switch to API-only mode for faster, lightweight responses. ### restore Restore the default CLI-based routing configuration. ## Architecture Messages flow through the OpenClaw Gateway, which reads the configured model provider and dispatches to the appropriate backend. CLI-based providers use the local Claude Code installation, while API providers make direct API calls. ## Troubleshooting | Issue | Fix | |-------|-----| | Config errors on restart | Run `openclaw doctor` to validate config | | Slow responses | Try switching to `sonnet` for faster responses | | Gateway issues | Check `~/.openclaw/logs/gateway.log` for details | | Falling back to secondary model | Primary backend may be unavailable — check logs |


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: yvette1226/lecture-transcript-study-notes (version 1.0.0)

--- name: Lecture Transcript to Study Notes description: Convert lecture transcripts into structured study notes, key concepts, and exam review summaries. version: 1.0.0 --- # Lecture Transcript to Study Notes ## Purpose This skill converts lecture transcripts into structured study materials. It helps students transform long lecture transcripts into: - clear study notes - key concepts - topic summaries - quick review material --- ## When to Use Use this skill when the user wants to: - summarize a lecture transcript - convert class recordings into notes - create study notes from transcripts - extract key concepts from lectures - prepare exam review material --- ## Input Users can provide: - lecture transcript - class recording transcript - seminar transcript - educational video transcript Optional context: - subject - course name - topic - instructor - exam focus --- ## Workflow 1. Read the transcript carefully. 2. Identify the main lecture topics. 3. Extract key concepts and definitions. 4. Identify examples explained by the lecturer. 5. Organize the information into structured study notes. 6. Highlight important concepts useful for exam review. --- ## Output Format ### Lecture Summary Short overview of the lecture. ### Key Concepts - list important concepts and definitions ### Main Topics - structured bullet points explaining each topic ### Important Examples Examples explained during the lecture. ### Quick Review Notes Short condensed notes for exam preparation. --- ## Important Rules - Do not invent information. - If a concept is unclear, mark it as **uncertain**. - Keep explanations concise and structured. - Prefer bullet points over long paragraphs. --- ## Tip Before using this skill, a transcript is required. Lecture transcripts can be generated using modern AI speech-to-text tools such as **AccurateScribe**, which converts audio or video recordings into text transcripts that can then be transformed into structured study notes using this skill. --- ## Example Requests Users may ask: - "Convert this lecture transcript into study notes" - "Summarize this class transcript" - "Extract key concepts from this lecture" - "Turn this transcript into exam review notes" When a transcript is provided, generate structured study notes.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: jpengcheng523-netizen/jpeng-calendar-sync (version 1.0.0)

--- name: jpeng-calendar-sync description: "Calendar synchronization skill. Sync events between Google Calendar, Outlook, and local storage. Supports CRUD operations and reminders." version: "1.0.0" author: "jpeng" tags: ["calendar", "google", "outlook", "scheduling", "events"] --- # Calendar Sync Synchronize calendar events across Google Calendar, Outlook, and local storage. ## When to Use - User wants to add/edit/delete calendar events - Sync events between different calendar providers - Set up reminders and recurring events - Check availability and schedule meetings ## Configuration ```bash # Google Calendar export GOOGLE_CLIENT_ID="xxx" export GOOGLE_CLIENT_SECRET="xxx" export GOOGLE_REDIRECT_URI="http://localhost:8080/callback" # Microsoft Outlook export OUTLOOK_CLIENT_ID="xxx" export OUTLOOK_CLIENT_SECRET="xxx" ``` ## Usage ### List events ```bash python3 scripts/calendar.py list --days 7 ``` ### Add event ```bash python3 scripts/calendar.py add \ --title "Team Meeting" \ --start "2024-01-15T10:00:00" \ --end "2024-01-15T11:00:00" \ --description "Weekly sync" \ --reminder 15 ``` ### Delete event ```bash python3 scripts/calendar.py delete --event-id "xxx" ``` ### Check availability ```bash python3 scripts/calendar.py available \ --date "2024-01-15" \ --duration 60 ``` ## Output ```json { "success": true, "event_id": "evt_xxx", "calendar_link": "https://calendar.google.com/..." } ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: frankieway/yuqing-sync-skill (version 1.1.0)

name: xiaoai_sync_to_bitable version: "2.0.0" description: > 从惠科/小爱数据接口增量拉取数据，写入飞书多维表。 支持单表 10000 条自动分表；不包含标注逻辑。 entrypoint: command: "python" args: - "sync_skill.py" inputs: - name: minutes type: integer required: false default: 60 description: 同步时间窗口，往前补偿的分钟数（基于当前时间） - name: folder_id type: integer required: false default: 763579 description: 小爱接口 folder_id - name: customer_id type: string required: false default: "xmxa" description: 小爱接口 customer_id - name: app_id type: string required: true description: 飞书开放平台应用 APP_ID - name: app_secret type: string required: true description: 飞书开放平台应用 APP_SECRET - name: xiaoai_token type: string required: true description: 小爱/惠科接口 token（Bearer 后面的部分） - name: bitable_url type: string required: true description: 目标飞书多维表视图链接（包含 base/app_token 和 table 参数） - name: xiaoai_base_url type: string required: false default: "http://wisers-data-service.wisersone.com.cn" description: 惠科/小爱 API 基础域名 outputs: - name: inserted_count type: integer description: 本次同步写入多维表的记录数 permissions: network: - "https://open.feishu.cn" - "http://wisers-data-service.wisersone.com.cn"


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: jobzhao15/huo15-mem (version 1.0.3)

--- name: huo15-mem / 火一五记忆 version: 1.0.0 description: 【版权：青岛火一五信息科技有限公司 账号：huo15】火一五记忆管理系统，按企微用户分类存储个人和公有记忆 author: Xun tags: [记忆, 用户, 分类, 火一五] --- # huo15-mem - 火一五记忆管理系统 按企微用户（chat_id）自动分类存储记忆。 ## 解决的问题 - 个人记忆 vs 公有记忆混在一起 - 多用户记忆无法隔离 - 管理员无法按用户清理记忆 ## 目录结构 ``` memory/ ├── shared/ # 公有记忆（所有用户共享） │ └── MEMORY.md ├── default/ # 默认用户 │ └── MEMORY.md ├── xun/ # Xun 个人记忆 │ └── MEMORY.md ├── ZhaoBo/ # 赵博个人记忆 │ └── MEMORY.md └── {其他用户}/ └── MEMORY.md ``` ## 激活条件 对话结束或用户说"记住xxx"时触发。 ## 判断逻辑 | 内容类型 | 存储位置 | |----------|----------| | 个人偏好/习惯 | `memory/{user}/MEMORY.md` | | 个人决策/总结 | `memory/{user}/MEMORY.md` | | 公司/项目知识 | `memory/shared/MEMORY.md` | | 多人经验总结 | `memory/shared/MEMORY.md` | | 技能使用经验 | `memory/shared/MEMORY.md` | ## 存入格式 ### 个人记忆 ```markdown # Xun 的记忆 - 偏好简洁回复风格 - 喜欢用语音讲故事 ``` ### 公有记忆（必须标注来源） ```markdown # 公有记忆 ## Xun存入 - 技能 file-organizer-zh 已安装 ## 赵博存入 - 常用数字人 Avatar ID: b2f84d86855349b6af0d0920f6597ec8 ``` ## 管理员清理 按用户清理公有记忆： ```bash # 搜索某用户的公有记忆 grep -n "## Xun存入" memory/shared/MEMORY.md # 删除某用户的公有记忆（需要保留其他用户内容） # 手动编辑或写脚本按章节删除 ``` ## 启动时加载 根据 `chat_id` 加载对应用户的记忆： - chat_id = "Xun" → 加载 `memory/xun/MEMORY.md` - chat_id 不存在 → 加载 `memory/default/MEMORY.md` - 同时加载 `memory/shared/MEMORY.md`（公有） ## 使用示例 - "记住我喜欢语音回复" → 存入个人记忆 - "这是所有人的经验" → 存入公有记忆，标注来源 - "整理工作区" → 不存记忆

path: _meta.json
content: ownerId: kn7b0rmtgvbq55rc54rhp69r79822ym9
slug: huo15-mem
version: 1.0.1
publishedAt: 1773454971944

Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: jackhua6/analyzing-financial-statements (version 1.0.0)

--- name: analyzing-financial-statements description: This skill calculates key financial ratios and metrics from financial statement data for investment analysis --- # Financial Ratio Calculator Skill This skill provides comprehensive financial ratio analysis for evaluating company performance, profitability, liquidity, and valuation. ## Capabilities Calculate and interpret: - **Profitability Ratios**: ROE, ROA, Gross Margin, Operating Margin, Net Margin - **Liquidity Ratios**: Current Ratio, Quick Ratio, Cash Ratio - **Leverage Ratios**: Debt-to-Equity, Interest Coverage, Debt Service Coverage - **Efficiency Ratios**: Asset Turnover, Inventory Turnover, Receivables Turnover - **Valuation Ratios**: P/E, P/B, P/S, EV/EBITDA, PEG - **Per-Share Metrics**: EPS, Book Value per Share, Dividend per Share ## How to Use 1. **Input Data**: Provide financial statement data (income statement, balance sheet, cash flow) 2. **Select Ratios**: Specify which ratios to calculate or use "all" for comprehensive analysis 3. **Interpretation**: The skill will calculate ratios and provide industry-standard interpretations ## Input Format Financial data can be provided as: - CSV with financial line items - JSON with structured financial statements - Text description of key financial figures - Excel files with financial statements ## Output Format Results include: - Calculated ratios with values - Industry benchmark comparisons (when available) - Trend analysis (if multiple periods provided) - Interpretation and insights - Excel report with formatted results ## Example Usage "Calculate key financial ratios for this company based on the attached financial statements" "What's the P/E ratio if the stock price is $50 and annual earnings are $2.50 per share?" "Analyze the liquidity position using the balance sheet data" ## Scripts - `calculate_ratios.py`: Main calculation engine for all financial ratios - `interpret_ratios.py`: Provides interpretation and benchmarking ## Best Practices 1. Always validate data completeness before calculations 2. Handle missing values appropriately (use industry averages or exclude) 3. Consider industry context when interpreting ratios 4. Include period comparisons for trend analysis 5. Flag unusual or concerning ratios ## Limitations - Requires accurate financial data - Industry benchmarks are general guidelines - Some ratios may not apply to all industries - Historical data doesn't guarantee future performance


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: zhangalexhy/quick-music (version 1.0.0)

--- name: quick-music description: 轻量快捷的音乐搜索工具。一条命令搜歌、拿播放链接，零依赖即开即用。 --- # Quick Music — 轻量找歌 ## 快速使用 ```bash node scripts/quick-music.js "周杰伦" node scripts/quick-music.js "晴天" --page 2 --limit 5 node scripts/quick-music.js "周杰伦" --play 1 ``` ## 参数说明 | 参数 | 说明 | 默认值 | |------|------|--------| | 第一个参数 | 搜索关键词（歌名/歌手） | 必填 | | `--page` | 搜索页码 | 1 | | `--limit` | 每页数量 | 10 | | `--play` | 获取第 N 首歌的播放链接 | 不获取 | ## 使用流程 1. 先搜索歌曲，会列出歌曲列表（序号、歌名、歌手） 2. 用 `--play N` 获取指定序号歌曲的播放链接 ## 示例 ```bash # 搜索周杰伦的歌 node scripts/quick-music.js "周杰伦" # 获取搜索结果中第 3 首的播放链接 node scripts/quick-music.js "周杰伦" --play 3 # 搜索特定歌曲 node scripts/quick-music.js "晴天" ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: ivangdavila/korean (version 1.0.0)

--- name: Korean description: Write Korean that sounds human. Not formal, not robotic, not AI-generated. --- ## The Real Problem AI Korean is technically correct but sounds off. Too formal. Too textbook. Too stiff. Natives write with contractions, particles, and casual endings. Match that. ## Formality Default Default register is too high. Casual Korean is the norm online. Unless explicitly formal: lean casual. 반말 is normal among peers. 존댓말 isn't always needed. ## Speech Levels Know the levels: - 합쇼체 (-습니다): very formal, news, presentations - 해요체 (-아/어요): polite, safe default, strangers - 해체/반말 (-아/어): casual, friends, peers - Online/texting: mostly 반말 or 해요체 - Don't mix levels awkwardly ## Contractions Casual Korean contracts heavily: - 하는 것 → 하는 거 - 무엇 → 뭐 - 그것 → 그거 - 나는 → 난 - 너는 → 넌 - 것이 → 게 - 아니야 → 아냐 ## Sentence Endings These add nuance: - ㅋㅋㅋ: laughter (more ㅋ = funnier) - ㅎㅎ: softer laugh - ㅠㅠ/ㅜㅜ: crying, sad - ~: softening (밥 먹었어~) - ㄱㄱ: 고고 (let's go) - ㅇㅇ: 응응 (yeah yeah) ## Particles Don't over-formal particles: - 을/를 often dropped in casual speech - 이/가 often dropped too - 은/는 sometimes dropped - Keep when needed for clarity ## Fillers & Flow Real Korean has fillers: - 음, 어, 그 - 아니 (sentence starter) - 근데, 그래서, 그러니까 - 막, 좀, 되게 - 진짜, 완전, 레알 ## Expressiveness Don't pick the safe word: - 좋다 → 대박, 미쳤다, 쩐다 - 나쁘다 → 별로, 최악, 구리다 - 많이 → 완전, 개, 존나 (crude) - 예쁘다 → 이쁘다, 존예 ## Internet Slang Modern Korean uses: - ㅋㅋㅋ, ㄹㅇ (레알/리얼) - 개 (intensifier): 개웃김, 개맛있어 - 존나 (crude intensifier) - 헐, 대박, 미쳤다 - 인정, 공감 - ㄴㄴ (노노), ㅇㅋ (오케이) ## Common Expressions Natural expressions: - 알겠어/알았어, ㅇㅇ - 뭐해?, 밥 먹었어? - 그치?, 맞아맞아 - 별로야, 그냥 그래 - 대박, 헐, 미쳤다 ## Reactions React naturally: - 진짜?, 헐, 대박 - 미쳤어?, 뭐야? - ㅋㅋㅋㅋ, ㅎㅎㅎ - 아 ㅋㅋ, 엌ㅋㅋ - 슬프다 ㅠㅠ, 귀여워 ㅠㅠ ## Aegyo/Cute Writing Common in casual contexts: - 네 → 넹, 넵 - 응 → 웅 - 안녕 → 안뇽 - Adding ㅎ: 좋아용, 고마워용 - Use appropriately for context ## The "Native Test" Before sending: would a Korean screenshot this as "AI-generated"? If yes—too formal, missing ㅋㅋ, no contractions. Casualize.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: abdullah944/quest-designer-skill (version 0.1.0)

--- name: "Quest Designer Skill" version: 0.1.0 slug: "quest-designer-skill" description: "Guides structured help for Quest Designer using clear templates, checks, and safe defaults (category: Game Design)." category: "Game Design" tags: - "game" - "openclaw" - "quest-designer" - "templates" generated: "2026-05-28" --- ## Purpose Guides structured help for Quest Designer using clear templates, checks, and safe defaults (category: Game Design). ## When to use - When you want structured guidance in the "Game Design" area. - When you need copy-paste-safe templates rather than improvised shell commands. - When you want repeatable prompts the agent can follow without external scraping. ## Safety rules - Do not collect passwords, OTPs, private keys, wallets, seeds, or session secrets. - Do not propose remote installers that execute unseen code or chained download-and-run snippets. - Keep outputs factual and reversible: prefer checklists over irreversible destructive actions. ## Inputs - Your goal in one paragraph (no secrets). - Optional constraints: audience, tone, length, deadline. - Optional pasted notes you own the rights to (keep PII minimal). ## Output format - A concise plan - Numbered checklist - Short next-actions list - Optional draft copy blocks you can edit ## Example prompts - Help me outline a concise plan using the Quest Designer approach. - Critique my draft outputs and suggest safer, clearer wording for Quest Designer. - Produce a checklist I can reuse weekly for Quest Designer without requesting private data. ## Support / Donate If this skill helps your workflow, you can support maintenance here: - PayPal: https://www.paypal.com/donate/?hosted_button_id=MJHCRZA9Z4X7Y


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)