OpenClaw/clawhub-security-signals huggingface dataset:
Skill: ivangdavila/english (version 1.0.1)

--- name: English description: Write English that sounds human. Not formal, not robotic, not AI-generated. --- ## The Real Problem AI English is technically correct but sounds off. Too formal. Too complete. Too polished. Natives write messier, shorter, more direct. Match that. ## Formality Default Default register is too high. Casual English is the norm—formal is the exception. Unless explicitly formal: lean casual. "Sure" not "Certainly". "Got it" not "Understood". ## Contractions Use them—always in casual contexts: - "I'm", "you're", "don't", "can't", "won't", "wouldn't" - Missing contractions = instant AI tell - "I am going to" → "I'm gonna" (very casual) or "I'm going to" ## Sentence Completeness Don't always complete sentences. Natives fragment: - "Coming?" "Yeah, one sec." - "You good?" "All good." - "Thoughts?" "Love it." - Let context carry weight. Less is more. ## Connectors Swap formal for natural: - "However" → "But" / "Though" - "Furthermore" → "Plus" / "Also" - "Therefore" → "So" - "In addition" → "And" / "On top of that" - "Nevertheless" → rarely used in casual speech ## Fillers & Flow Real English has fillers. Use them in casual contexts: - "Like", "you know", "I mean", "basically" - "So yeah", "anyway", "right?" - "Honestly", "actually", "literally" (even when not literal) - Missing these = textbook English ## Expressiveness Don't pick the safe word. English is expressive: - "Good" → "Great" / "Awesome" / "Solid" / "Fire" - "Bad" → "Terrible" / "Awful" / "Trash" / "Mid" - "Big" → "Huge" / "Massive" / "Insane" - Amplify when context calls for it ## Politeness Calibration AI over-polishes. Natives are more direct: - ❌ "I would be delighted to assist you with that" - ✓ "Sure, I can help" - ❌ "Would you mind if I..." - ✓ "Can I..." / "Mind if I..." - Match politeness to relationship, not maximum ## Idioms & Expressions Use natural expressions: - "No worries", "my bad", "fair enough" - "That tracks", "makes sense", "I'm down" - "Lowkey", "highkey", "dead serious" - "It is what it is", "at the end of the day" ## Reactions React like a human: - "Wait what", "No way", "Seriously?" - "That's wild", "Damn", "Holy shit" (context appropriate) - "Lol", "lmao", "haha" in text - "Nice!", "Sick!", "Let's go!" ## Regional Awareness If region known, commit: - US: "apartment", "trash", "gotten", "I could care less" - UK: "flat", "rubbish", "got", "I couldn't care less", "proper", "brilliant" - Aus: "reckon", "heaps", "arvo", "no worries" - Don't mix. Stay consistent. ## The "Native Test" Before sending: would someone screenshot this as "AI-generated"? If yes—too clean, too formal, too perfect. Rough it up.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: erongcao/erong-okx-trading-analyst (version 1.0.0)

--- name: okx-trading-analyst description: OKX加密货币技术分析工具 — 使用欧易API获取实时行情数据，计算技术指标（MA、MACD、RSI、布林带等），生成交易信号。当用户需要加密货币行情分析、技术指标计算、或交易信号时触发此skill。 --- # OKX Trading Analyst 使用欧易OKX API进行加密货币技术分析和交易信号生成。 ## API配置 你需要在 OKX 交易所申请 API Key（只需要**读取权限**即可），然后在项目根目录创建 `.env` 文件： ```env OKX_API_KEY=your-api-key-here OKX_API_SECRET=your-api-secret-here ``` OKX 公开接口免费使用，不需要签名认证，只需要 API Key 即可。 **权限要求**: 仅需要行情读取权限，不要给交易权限。 ## 功能 - **实时数据**: 获取OKX K线数据和最新行情 - **技术指标**: MA、MACD、RSI、布林带、ATR - **交易信号**: 综合评分系统，生成买卖建议 - **多周期**: 支持1m/5m/15m/30m/1H/4H/1D等周期 ## 使用方法 ### 命令行 ```bash # 分析BTC 4小时周期 python3 scripts/okx_analyst.py BTC-USDT # 分析ETH 1小时周期 python3 scripts/okx_analyst.py ETH-USDT --timeframe 1H # 只输出交易信号 python3 scripts/okx_analyst.py BTC-USDT --signal-only ``` ### Python调用 ```python from scripts.okx_analyst import OKXAnalyzer analyzer = OKXAnalyzer() # 获取数据并分析 df = analyzer.get_klines("BTC-USDT", bar="4H", limit=200) df = analyzer.calculate_indicators(df) signals = analyzer.generate_signals(df) print(f"信号: {signals['recommendation']['signal']}") print(f"强度: {signals['strength']}/+10") ``` ## 输出示例 ``` ============================================================ 📊 BTC-USDT 技术分析报告 (4H周期) ============================================================ 【价格信息】 当前价格: $67,423.50 【交易信号】 🟢 温和看涨 (强度: +3/+10) 建议操作: 轻仓试多 止损: $65,423 (-3%) 目标: $70,795 (+5%) 信号详情: ✅ [趋势] MA20 > MA60，中长期趋势向上 ✅ [趋势] 价格站上MA20短期均线 ✅ [动量] MACD金叉，动量转强 ℹ️ [动量] RSI中性 (58.32) ============================================================ ``` ## 信号说明 | 强度 | 信号 | 建议 | |:---:|:---:|:---| | +5以上 | 🟢 强烈看涨 | 逢低做多 | | +2~+4 | 🟡 温和看涨 | 轻仓试多 | | -1~+1 | ⚪ 中性 | 观望 | | -2~-4 | 🟠 温和看跌 | 轻仓试空 | | -5以下 | 🔴 强烈看跌 | 逢高做空 | ## 风险提示 ⚠️ 技术分析仅供参考，不构成投资建议。加密货币市场波动剧烈，请严格设置止损。 ## 依赖 ```bash pip install requests pandas numpy ``` ## 文件结构 ``` okx-trading-analyst/ ├── SKILL.md └── scripts/ └── okx_analyst.py ```

path: _meta.json
content: ownerId: kn7c4q39hrf57j94gsf0jt1t2n82pzds
slug: erong-okx-trading-analyst
version: 1.0.0
publishedAt: 1744178400000

path: scripts/__init__.py
content: # OKX Trading Analyst Package


Security scan verdicts — ClawScan: suspicious | static analysis: suspicious | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: bytesagain3/dcs (version 1.0.0)

--- name: "dcs" version: "1.0.0" description: "Distributed control system manager" author: "BytesAgain" homepage: "https://bytesagain.com" source: "https://github.com/bytesagain/ai-skills" tags: [dcs, industrial, cli, tool] category: "industrial" --- # dcs Distributed control system manager ## Commands ### `status` ```bash scripts/script.sh status ``` Show current status ### `add` ```bash scripts/script.sh add ``` Add new entry ### `list` ```bash scripts/script.sh list ``` List all entries ### `search` ```bash scripts/script.sh search ``` Search entries ### `remove` ```bash scripts/script.sh remove ``` Remove entry by number ### `export` ```bash scripts/script.sh export ``` Export data to file ### `stats` ```bash scripts/script.sh stats ``` Show statistics ### `config` ```bash scripts/script.sh config ``` View or set config ### `help` ```bash scripts/script.sh help ``` ### `version` ```bash scripts/script.sh version ``` ## Configuration Use `scripts/script.sh config <key> <value>` to set preferences. | Variable | Required | Description | |----------|----------|-------------| | `DCS_DIR` | No | Data directory (default: ~/.dcs/) | ## Data Storage All data stored in `~/.dcs/` using JSONL format (one JSON object per line). ## Output Structured output to stdout. Exit code 0 on success, 1 on error. --- *Powered by BytesAgain | bytesagain.com | [REDACTED_SECRET]*


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: codenova58/buffets (version 0.1.0)

--- name: "网红自助餐" description: "提供关于网红自助餐的推荐清单、打卡路线与指南。用户搜索网红自助餐或规划相关出行时调用。" --- # 网红自助餐 ## 筛选项 - 城市/商圈/交通便利度 - 人均预算/排队时长/是否可预约 - 菜系/口味（辣度、清淡）/素食或清真 - 卫生评分/儿童友好/无障碍设施 ## 返回字段 - 店名/亮点（签名菜、特色）/人均/评分/排队 - 地址/营业时间/预约方式/是否外卖/氛围类型 - 实时热度/最佳到访时段/避坑提示 ## 路线建议 - 同商圈串联3-5家/步行与地铁优先 - 高峰期替代方案/雨天备选/亲子与情侣偏好 ## 示例请求 - “重庆 网红自助餐 辣度友好清单（人均≤80）” - “广州 网红自助餐 不排队TOP10（可预约）” ## 更新频率 - 每周迭代，结合新热度与口碑反馈 ## 注意事项 - 高峰期排队较久，建议提前预约或错峰 - 部分项目有拍摄限制或最低消费，按现场规则执行


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

--- name: Slovenian description: Write Slovenian that sounds human. Not formal, not robotic, not AI-generated. --- ## The Real Problem AI Slovenian is technically correct but sounds off. Too formal. Too literary. Natives write more casually, with particles and warmth. Match that. ## Formality Default Default register is too high. Casual Slovenian is warm and direct. Unless explicitly formal: lean casual. "Živjo" or "Hej" not "Dober dan". "Ja" not "Da, seveda". ## Ti vs Vi Critical distinction: - Vi: formal, elderly, professional - Ti: friends, peers, internet, casual - Slovenian internet uses ti - Overusing vi = stiff ## Dual Form Slovenian has dual (for two people): - Midva (we two), vidva (you two) - Use it correctly—it's distinctive - But casual writing sometimes skips it ## Particles & Softeners These make Slovenian natural: - No: filler, "well" ("No, ne vem") - Pač: "just", "simply" - Že: emphasis, "already" - A: question particle - Saj: "after all" ## Fillers & Flow Real Slovenian has fillers: - No, torej, pač - Kao, tip - Veš, poslušaj - Pravzaprav, sicer ## Expressiveness Don't pick the safe word: - Dobro → Super, Odlično, Kul - Slabo → Grozno, Zanič, Bedno - Zelo → Ful, Mega, Res ## Common Expressions Natural expressions: - Okej, Jasno, Kul - Ni panike, Brez skrbi - Resno?, Res?, Kaj? - Super!, Odlično!, Top! ## Reactions React naturally: - Resno?, Res?, A ni res! - Ojoj!, Vau!, Bože! - Super!, Kul!, Ekstra! - Haha, lol in text ## The "Native Test" Before sending: would a Slovenian screenshot this as "AI-generated"? If yes—too formal, no "no", too stiff. Add casual warmth.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: hanxiaolin/idea-inbox (version 1.1.1)

--- name: idea-inbox description: 收集“idea:/灵感：”消息到飞书多维表格（默认自动创建新表），用大模型生成AI归纳/类别/标签（支持自动新增标签），并按配置的每日时间（默认10:02，今日新增=0不发）推送当日汇总。 --- # 灵感妙计（Idea Inbox） 把你在飞书私聊里随手发来的想法收集成结构化的灵感池，并自动分类，方便后续筛选与推进。 ## Triggers - 以 `idea:` 开头的消息 - 以 `灵感：` 开头的消息 > 仅在飞书私聊生效。 ## Use Cases - 你随手发一个想法：我自动入库并分类 - 你持续积累一周：我每天 10:02 给你发当日新增汇总（若当日 0 新增则不发） ## Data Store - 默认：首次运行（第一次发 `idea:`/`灵感：`）自动创建一个新的飞书多维表格（Bitable）App：`灵感妙计`。 - 创建完成后，会把 `app_token/table_id/字段id` 等写入本地配置文件： - `~/.openclaw/idea-inbox/config.json` 字段（默认）：内容 / AI归纳 / 类别 / 标签 / 状态 / 来源 / 创建时间 ## Configuration `~/.openclaw/idea-inbox/config.json`（自动生成，可手改）示例： ```json { "prefixes": ["idea:", "灵感："], "daily_time": "10:02", "bitable": { "app_token": "...", "table_id": "...", "fields": { "content": "内容", "ai_summary": "AI归纳", "category": "类别", "tags": "标签", "status": "状态", "source": "来源", "created_time": "创建时间" } }, "model": { "mode": "codex_files_first", "fallback": null }, "tags": { "auto_add": true, "max_tags": 5 }, "status": { "options": ["待处理", "已处理", "无法处理"], "default": "待处理" } } ``` - `daily_time`：仅需配置每日时间；`send_if_zero` 固定为 false（0 新增不发）。 - 模型：默认优先读取 `~/.codex/auth.json` + `~/.codex/config.toml`（不读 env）。 - 若用户没有 codex 文件，可在 `model.fallback` 填 `baseUrl/apiKey/apiType/model`。 ## Inputs - Required: - `text`: 原始消息文本（包含前缀） - `chat_type`: 需为 direct/p2p（私聊） ## Outputs - 成功：写入一条记录到 Bitable，并返回 record_id - 失败：返回错误原因（网络/权限/字段缺失/模型调用失败等） ## Workflow 1. 校验触发条件（私聊 + 前缀匹配） 2. 抽取原文内容（去掉前缀） 3. 调用大模型生成严格 JSON：{category,tags,summary} 4. 标签自动新增：若 tags 不在 Bitable 选项中，先追加选项 5. 写入 Bitable：内容/AI归纳/类别/标签/状态=收集箱/来源=飞书私聊 6. 每日 10:02 汇总：统计当日新增，>0 才推送 ## Limitations - 本技能不处理群聊消息 - 标签自动新增会带来标签膨胀；可后续加“标签黑名单/合并”规则 - 模型输出需严格 JSON；会做枚举校验与截断


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: jochoonhwan/korean-resume-builder (version 1.0.0)

--- name: korean-resume-builder description: 한국式 이력서와 자기소개서를 작성합니다. 다음 경우에 사용: (1) 취업 준비 중인 사람, (2) 이력서 양식이나写法이 필요한 경우, (3) 자기소개서 컨설팅이 필요한 경우, (4) 한국 채용 프로세스에 맞는 문서가 필요한 경우. 지원 직종, 경력 사항, 보유 기술을 기반으로 맞춤 이력서와자기소개를 생성합니다. --- # 🇰🇷 한국 이력서/자기소개서 빌더 ## 개요 한국 채용 시장에 최적화된 전문 이력서와 자기소개서를 작성합니다. 한국 기업 문화와 채용 프로세스를 고려하여:a0eda 형태로 제공합니다. ## 사용 방법 사용자에게 다음 정보를 수집: 1. **성명**, **연락처**, **이메일** 2. **지원 직종/직무** (예: 서비스 기획, 마케팅, 개발 등) 3. **경력 사항** (신입/경력, 회사명, 기간, 담당 업무) 4. ** 보유 기술** (하드스킬, Sofskills) 5. **학력** (학교, 학과, 재학 기간) 6. **奖项/자격증** (해당 시) 7. **하고 싶은 말** (핵심 가치관,の強み) ## 출력물 ### 1. 이력서 (Resume/CV) ```markdown # 이력서 ## 기본 정보 - 성명: [이름] - 연락처: [전화번호] - 이메일: [이메일] ## 학력 - [학교명] / [학과] / [학위] / [기간] ## 경력 - [회사명] / [직함] / [기간] - 담당 업무 1 - 담당 업무 2 ## 보유 기술 - 기술 1, 기술 2, 기술 3 ##奖项/자격증 - 자격증 1 / 취득 연도 -奖项 1 / 수상 연도 ``` ### 2. 자기소개서 (Cover Letter) 한국 기업은 보통 500-1000자 분량의 자기소개를 요청합니다. 다음 구조로 작성: **구조:** 1. **서론** (100-150자): 지원 동기와 회사를 알게 된 경로 2. **본론1** (200-300자): 지원 직무와 관련된 경험/스킬 3. **본론2** (200-300자): 나의 강점과 가치관, 회사에 기여할 방법 4. **결론** (50-100자): 마무리 멘트 ## 한국 이력서 특징 ### 양식 포인트 -*A4 1장以内*에 정리 - 파일명: `이름_지원직무_이력서.pdf` - Tahoma나 Arial 폰트 사용 (가독성) -页边距: 위/아래 20mm, 왼쪽/오른쪽 25mm ### 핵심 원칙 1. **한눈에 들어오는 가독성**: 핵심 정보 스캔하기easy 2. **量化된 경험**: "업무 수행" X → "월 100건 고객対応" O 3. **지원 직무 맞춤**: 지원하는 직종의 핵심 역량 강조 4. **빈칸 없는 깔끔함**: 설명不能 빈칸 만들기 ## 자기소개서 팁 ### 한국 기업별 선호 양식 - **대기업**: 서류 전형中心, 자기소개서 2-3개 필수 - **중소기업**: 면접中心, 이력서 위주 - **스타트업**: 역량 중심, 자유 양식 ###避けるべき 것 - 너무 긴 문장 (1문장 50자以下) - 일반적인 표현 ("열정적이다", "노력한다") - 타인과의 비교 ("남들보다") - 잘못된 정보/거짓 ### ✓ 좋은 표현 - "구체적으로" → 수치로 증명 - "팀을 위해" → 구체적 기여 - "성장했다" → 어떻게 성장했는지


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: akkualle/akkualle-keyword-research (version 1.0.0)

--- name: keyword-research description: "SEO Keyword Research Tool für high-value Keywords mit Search Intent Analysis, Difficulty Assessment und Content Opportunity Mapping." version: "1.0.0" author: "AkkuAlle" price: "19€" license: "commercial" emoji: 🔑 user-invocable: true tags: - seo - keywords - research - content - ranking --- # 🔑 Keyword Research Tool **Finde die besten Keywords für deinen Content.** ## ✨ Features | Funktion | Beschreibung | |----------|--------------| | **Keyword Discovery** | High-Value Keywords finden | | **Search Intent** | Intent-Analyse (Informational, Commercial, Transactional) | | **Difficulty Score** | Wie schwer ist das Keyword zu ranken? | | **Volume Check** | Monatliches Suchvolumen | | **Opportunity Mapping** | Content-Ideen generieren | ## 🚀 Verwendung ```bash # Keyword recherchieren keyword-research "e scooter kaufen" # Bulk-Analyse keyword-research --file keywords.txt # Mit Difficulty keyword-research "keyword" --difficulty ``` ## 💰 Preis: 19€ --- *Version: 1.0.0 | Author: AkkuAlle*


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: googleworkspace-bot/recipe-backup-sheet-as-csv (version 1.0.13)

--- name: recipe-backup-sheet-as-csv description: "Export a Google Sheets spreadsheet as a CSV file for local backup or processing." metadata: version: 0.22.5 openclaw: category: "recipe" domain: "productivity" requires: bins: - gws skills: - gws-sheets - gws-drive --- # Export a Google Sheet as CSV > **PREREQUISITE:** Load the following skills to execute this recipe: `gws-sheets`, `gws-drive` Export a Google Sheets spreadsheet as a CSV file for local backup or processing. ## Steps 1. Get spreadsheet details: `gws sheets spreadsheets get --params '{"spreadsheetId": "SHEET_ID"}'` 2. Export as CSV: `gws drive files export --params '{"fileId": "SHEET_ID", "mimeType": "text/csv"}'` 3. Or read values directly: `gws sheets +read --spreadsheet SHEET_ID --range 'Sheet1' --format csv`


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: shenghoo123-png/kay-juejin-tools-v2 (version 1.0.0)

# 掘金发布技能 ## 1. 平台简介 掘金是一个面向程序员的技术社区平台，专注于分享技术文章、教程、实战经验。用户可以通过写文章积累粉丝、建立个人品牌，优质内容有机会获得官方推荐和流量扶持。 **网址**: https://juejin.cn --- ## 2. 注册/登录方式 ### 注册方式 - **手机号注册**：输入手机号 + 验证码 - **邮箱注册**：掘金暂不支持纯邮箱注册，建议用手机号 - **第三方登录**：支持 Github / 微信 / 微博 登录 ### 登录入口 - 首页右上角「登录/注册」 - 推荐使用 Github 登录（技术身份更匹配） --- ## 3. 写文章/发布文章流程 ### 步骤一：进入创作页面 1. 登录后，点击右上角「写文章」或头像下拉菜单 → 「写文章」 2. 进入在线编辑器页面 ### 步骤二：编辑文章 1. **标题**：输入文章标题（建议20-40字，包含核心关键词） 2. **正文**：使用 Markdown 编辑器编写 3. **封面图**：上传封面图（可选，不上传会使用默认封面） 4. **分类**：选择文章分类（如：前端 / 后端 / Android / iOS / 人工智能 等） 5. **标签**：添加1-5个标签（如：Python、Vue、Redis等），方便被搜索到 6. **专栏**：可选择加入专栏（需先创建专栏） ### 步骤三：预览与发布 1. 点击「预览」查看效果 2. 确认无误后，点击「发布」 3. 文章审核通过后公开可见（通常几分钟内） ### 草稿保存 - 文章会自动保存为草稿 - 可在「创作中心」→「我的文章」中找到 --- ## 4. 文章模板 ### 文章标题模板 ``` [核心技术点] + [应用场景/价值] + [文章类型] 示例： Python 异步编程完全指南（asyncio 实战） Vue3 + Vite 构建生产级项目的最佳实践 从0到1：如何设计高可用的微服务架构 ``` ### 文章正文模板（Markdown） ```markdown # [文章标题] [一句话介绍这篇文章解决的问题或价值，100字以内] ## 背景 [介绍为什么要写这篇文章，读者能获得什么] ## 目录 - [章节1] - [章节2] - [章节3] --- ## 第一节：[章节标题] [正文内容] ### 1.1 [小节标题] [代码块/示例] ```python # 示例代码 def hello(): print("Hello, World!") ``` ## 总结 [回顾全文要点，列出关键结论] ## 参考资料 - [参考资料1链接] - [参考资料2链接] ``` ### 文章开头模板（吸引点击） ``` 作为[职业/身份]，我在实际项目中遇到了[问题]。 这篇文章会手把手教你[解决什么]，通过[方法/工具]，实现[效果]。 读完本文，你将掌握：[技能点1]、[技能点2]、[技能点3]。 ``` --- ## 5. 注意事项 1. **标题决定点击率**：避免标题党，但要足够吸引，用数字/对比/疑问更有效果 2. **代码要规范**：代码块标明语言，注释清晰，避免截图代码 3. **图片要规范**：图片建议使用图床链接，避免使用本地图片导致无法显示 4. **内容原创性**：掘金重视原创，搬运内容会被下架 5. **首发有优势**：首发文章更容易获得推荐 6. **排版要美观**：善用 Markdown（标题层级、列表、引用、代码块） 7. **标签要精准**：选对标签能带来精准流量 --- ## 6. 常见问题 **Q: 文章有收益吗？** A：掘金有「掘金人气榜」等活动，优质文章可获得奖金。创作激励计划需申请加入。 **Q: 如何获得更多阅读量？** A：积极互动（评论、点赞）、选好标签和分类、发布时间选晚8-10点、标题优化。 **Q: 可以转载文章吗？** A：可以，但需注明原文出处，且需获得原作者授权。 **Q: 文章被删了怎么办？** A：查看站内信中的违规原因，根据原因修改后重新发布。 **Q: 如何创建专栏？** A：在「创作中心」→「我的专栏」中创建，专栏需要至少3篇文章才能申请。


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: twolf01/nano-web-search (version 1.2.3)

--- name: nano-web-search description: AI-powered web search via NanoGPT API with multiple providers (linkup, tavily, exa, kagi, perplexity, valyu, brave). Supports searchResults, sourcedAnswer, and structured output formats. homepage: https://nano-gpt.com metadata: {"clawdbot":{"requires":{"bins":["python3","curl"],"packages":["requests"],"env":["NANOGPT_API_KEY"]},"primaryEnv":"NANOGPT_API_KEY"}} --- # NanoGPT Web Search AI-powered web search via NanoGPT API with multiple providers. ## Requirements - `python3` - For payload building and output formatting - `curl` - For HTTP requests - `requests` Python package - For Python API usage ## Setup Install the requests package: ```bash pip install requests ``` Set your NanoGPT API key as an environment variable: ```bash export NANOGPT_API_KEY="sk-nano-your-key-here" ``` Get your API key from [nano-gpt.com](https://nano-gpt.com). ## Usage ```bash # Basic search ./search.sh "your query" # With specific provider ./search.sh "AI trends 2025" --provider tavily # Deep search ./search.sh "quantum computing" --depth deep # Search with date filter ./search.sh "climate news" --from-date 2025-01-01 --to-date 2025-02-18 # Sourced answer (synthesized response with citations) ./search.sh "what is RAG" --output-type sourcedAnswer # JSON output (for scripting) ./search.sh "python tutorials" --json ``` ## Providers - `linkup` (default) - $0.006 standard, $0.06 deep - `tavily` - $0.008 standard, $0.016 deep - `exa` - $0.005 base + per-page - `kagi` - $0.002 web/news, $0.025 search - `perplexity` - $0.005 flat - `valyu` - ~$0.0015/result - `brave` - $0.005 flat ## Options - `--provider` - Search provider (default: linkup) - `--depth` - Search depth: standard or deep - `--output-type` - Output format: searchResults, sourcedAnswer, structured - `--from-date` - Start date filter (YYYY-MM-DD) - `--to-date` - End date filter (YYYY-MM-DD) - `--include-domains` - Comma-separated domains to include - `--exclude-domains` - Comma-separated domains to exclude - `--max-results` - Max results (provider-specific) - `--json` - Output raw JSON ## Python API ```python from search import NanoWebSearch # Pass API key explicitly (recommended) search = NanoWebSearch([REDACTED_SECRET]") # Or use NANOGPT_API_KEY environment variable search = NanoWebSearch() results = search.search("AI trends", provider="tavily", depth="deep") for r in results['data']: print(f"{r['title']}: {r['url']}") ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: yzdame/mistral-ocr (version 1.0.4)

--- name: mistral-ocr description: "Convert PDF/images to Markdown/JSON/HTML using Mistral OCR API. Supports image extraction, table recognition, header/footer handling, and multi-column layouts. Usage: Upload a file and say Use Mistral OCR to process this." registry: homepage: https://github.com/YZDame/Mistral-OCR-SKILL author: YZDame credentials: required: true env_vars: - MISTRAL_API_KEY --- # ⚠️ Privacy Warning - 隐私警告 **IMPORTANT - READ BEFORE INSTALLING:** This skill **uploads your files to Mistral's cloud servers** for OCR processing. **Do NOT use with sensitive or confidential documents** unless: - You trust Mistral's data handling policies - You have reviewed Mistral's privacy policy - You accept that file contents will be transmitted and processed remotely **For sensitive documents, use offline/local OCR tools instead.** --- # Mistral OCR Skill A powerful OCR tool that converts PDF files and images into Markdown, JSON, or HTML formats using Mistral's state-of-the-art OCR API. ## Installation ```bash # Clone or download this repository git clone https://github.com/YZDame/Mistral-OCR-SKILL.git cd Mistral-OCR-SKILL # Install dependencies pip install -r requirements.txt ``` ## 🔑 API Key Setup (Required) **Get your API key:** 👉 https://console.mistral.ai/home **Set the environment variable:** ```bash export MISTRAL_API_KEY=your_api_key ``` ## CLI Usage ```bash cd scripts # Process PDF to Markdown python3 mistral_ocr.py -i input.pdf # Process PDF to JSON python3 mistral_ocr.py -i input.pdf -f json # Specify output directory python3 mistral_ocr.py -i input.pdf -o ~/my_ocr_results ``` ## Arguments | Flag | Description | |------|-------------| | `-i, --input` | Input file path (required) | | `-f, --format` | Output format: markdown/json/html (default: markdown) | | `-o, --output` | Output directory | ## Data Privacy **What happens to your files:** 1. Files are uploaded to Mistral's OCR API 2. Files are processed on Mistral servers 3. Processing results are returned to you 4. Files are not stored on Mistral servers (per Mistral policy) **For more details, see:** https://mistral.ai/privacy-policy ## License MIT

path: requirements.txt
content: mistralai>=0.0.9


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: albionaiinc-del/clean-filenames (version 1.0.0)

# Clean Filenames Strips invalid characters, normalizes whitespace, and safely renames files to ensure cross-platform compatibility and professional organization. ## Usage ```bash # Clean files in current directory clean_filenames # Clean files in specific directory clean_filenames ~/Documents/Downloads # Recursively clean all subdirectories clean_filenames ~/Photos -r # Clean a single file clean_filenames "broken file name: 2023?.jpg" ``` ## Price $2.50


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