OpenClaw/clawhub-security-signals huggingface dataset:
Skill: zhangqiang327/qingbo-search (version 1.0.1)

# 清博开放平台文章搜索 Skill ## 功能说明 通过清博开放平台的关键词检索文章接口，帮助用户搜索全网文章舆情信息。用户可以根据关键词、时间范围、媒体类型等条件进行检索，并获取文章标题、URL、发布时间等信息。 ## 配置说明 ### 1. 注册开发者账号 - 访问清博开放平台官网注册账号 - 登录后创建应用，获取 `app_key` 和 `app_secret` ### 2. 配置文件 在 `config.json` 文件中配置以下参数： ```json { "app_key": "您的app_key", "app_secret": "您的app_secret" } ``` ## 使用方法 ### 基本搜索 输入包含关键词的查询语句，如： - "搜索关于人工智能的文章" - "查找2024年1月的科技新闻" ### 高级搜索 可以指定时间范围、平台类型等条件，如： - "搜索2024年1-3月微信平台关于人工智能的文章" - "查找最近一周微博上的经济相关新闻" ### 统计分析 可以请求统计信息，如： - "统计2024年关于人工智能的文章数量" - "分析2024年1月科技新闻的媒体分布" ## 接口说明 ### 关键词检索文章接口 - API地址：`/pubsent/full-search/index` - 请求方式：GET - 主要参数： - keywords_include：关键词（必填） - posttime_start：开始时间（可选） - posttime_end：结束时间（可选） - media_type：媒体类型（可选） - news_emotion：情感属性（可选） - refer_province：省份（可选） - order：排序方式（可选） - sort：排序字段（可选） - page：页码（可选） - limit：每页数量（可选） ### 响应示例 ```json { "success": true, "data": { "newsList": [ { "news_title": "文章标题", "news_url": "文章URL", "news_posttime": "发布时间", "media_type": "媒体类型", "media_name": "媒体名称" } ], "numFound": 100 } } ``` ## 技术实现 ### 关键词提取 使用自然语言处理技术分析用户输入语句，提取关键词、时间范围、平台类型等参数。 ### 接口调用 - 签名生成：按照清博API鉴权机制生成请求签名 - 请求发送：发送HTTP请求到清博API接口 - 响应处理：解析API返回的JSON数据 ### 结果呈现 根据用户输入的实际需求，返回文章标题、URL、时间等信息，或统计文章总量进行分析。 ## 注意事项 - 接口调用会消耗清博平台点数，请合理使用 - 每个接口调用有参数限制，如关键词数量、时间范围等 - 接口返回数据可能包含重复或相似文章（通过sim_hash字段识别）


Security scan verdicts — ClawScan: clean | static analysis: suspicious | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: jikeapi-cn/jike-word-query (version 1.0.0)

--- name: jike-word-query description: 汉语词语查询。支持搜索词语、词语详情、随机词语、近义词查询和反义词查询，返回词语、拼音、解释、出处、例句、故事、用法、近义词和反义词。适用场景：用户说“查一下太公钓鱼是什么意思”“一言相关词语”“伟大的近义词”“高兴的反义词”等。数据由即刻数据（jikeapi.cn）开放接口提供。 homepage: https://www.jikeapi.cn/ metadata: {"openclaw":{"emoji":"📝","requires":{"bins":["python3"],"env":["JIKE_WORD_QUERY_KEY"]},"primaryEnv":"JIKE_WORD_QUERY_KEY"}} --- # 汉语词语查询 - 即刻数据 > 数据由 **[即刻数据](https://www.jikeapi.cn/)** 提供，帮助 AI 客户端快速接入可靠数据服务。 支持：**词语搜索、词语详情、随机词语、近义词查询、反义词查询**。 ## 前置配置 ```bash export JIKE_WORD_QUERY_KEY=你的AppKey # 或使用通用 Key export JIKE_APPKEY=你的AppKey ``` ## 使用方法 ```bash python3 scripts/word_query.py search --keyword 一言 --page-size 5 python3 scripts/word_query.py detail --id 75046 python3 scripts/word_query.py random python3 scripts/word_query.py similar --word 伟大 python3 scripts/word_query.py opposite --word 高兴 python3 scripts/word_query.py similar --word 伟大 --json ``` ## AI 使用步骤 1. 用户按关键词找词语时，使用 `search` 子命令。 2. 用户问词语解释、出处、用法时，优先搜索获取 ID，再用 `detail` 查询详情。 3. 用户要求随机词语时，使用 `random` 子命令。 4. 用户问近义词时，使用 `similar` 子命令。 5. 用户问反义词时，使用 `opposite` 子命令。 ## 返回字段 | 字段 | 含义 | | --- | --- | | `id` | 词语 ID | | `word` | 词语 | | `pinyin` | 拼音 | | `explanation` | 解释 | | `source_book` | 出处书名 | | `source_text` | 出处原文 | | `example_text` | 例句 | | `usage` | 用法 | | `similar` | 近义词 | | `opposite` | 反义词 | ## 脚本位置 `scripts/word_query.py`


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

--- name: "网红卤味" description: "提供关于网红卤味的推荐清单、打卡路线与指南。用户搜索网红卤味或规划相关出行时调用。" --- # 网红卤味 ## 适用场景 - 用户搜索网红卤味或规划相关出行时调用 - 需要获取网红卤味的推荐清单、打卡路线与简要指南 ## 使用方式 - 输入城市或区域，可筛选主题、预算、时段 - 支持返回快速路线建议与人气分级 ## 返回内容 - 推荐清单：名称/亮点/地址/时间/人气 - 路线草案：交通方式/用时/顺序/避坑提示 - 注意事项：预约/排队时长/最佳时段/费用范围 ## 示例请求 - “成都 网红卤味 一日打卡路线” - “上海适合情侣的 网红卤味 TOP10” ## 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 ## 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: coolhackboy/poyo-kling-2-6-motion-control (version 1.0.0)

--- name: poyo-kling-2-6-motion-control description: Kling 2.6 Motion Control on PoYo / poyo.ai via `https://api.poyo.ai/api/generate/submit`; use for `kling-2.6-motion-control`, motion transfer, character animation, orientation control, and 720p/1080p output. metadata: {"openclaw": {"homepage": "https://docs.poyo.ai/api-manual/video-series/kling-2.6-motion-control", "requires": {"bins": ["curl"], "env": ["POYO_API_KEY"]}, "primaryEnv": "POYO_API_KEY"}} --- # PoYo Kling 2.6 Motion Control Use this skill for `kling-2.6-motion-control` jobs on PoYo. It is for strict motion transfer workflows that require both a character image and a reference video. ## Use When - The user explicitly asks for `Kling 2.6 Motion Control` or `kling-2.6-motion-control`. - The task is motion transfer from a reference video to a target character image. - The workflow depends on `character_orientation` and explicit resolution control. ## Core Capability - `kling-2.6-motion-control` is not a general video model. Use it only when the task requires character animation from a supplied image plus a supplied motion video. ## Key Inputs - `image_urls` is required, supports one character image, and should clearly show head, shoulders, and torso. - `video_urls` is required, supports one reference video, and must be 3-30 seconds. - `character_orientation` is required and supports `image` or `video`. - `resolution` is required and supports `720p` or `1080p`. - `prompt` is optional scene guidance only. ## Execution - Read `references/api.md` for endpoint details, model ids, key fields, example payloads, and polling notes. - Use `scripts/submit_kling_2_6_motion_control.sh` to submit a raw JSON payload from the shell. - If the user only needs a curl example, adapt the example from `references/api.md` instead of rewriting from scratch. - After submission, report the `task_id` clearly so follow-up polling is easy. ## Output expectations When helping with this model family, include: - chosen model id - final payload or a concise parameter summary - whether reference images are involved - returned `task_id` if a request was actually submitted - next step: poll status or wait for webhook


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: phil-osophy-42/slug (version 1.0.0)

--- name: corporate-ppt-generator version: 1.0.2 description: Generate PPT decks from prompts/block XML while preserving corporate brand style. categories: - productivity - presentation --- # Corporate PPT Generator ## Description Generate a new `.pptx` by reusing existing template slides from `PPT_Template.pptx`. The runtime is XML-only and prioritizes template-first rendering. ## When To Use Use this skill when the user asks: - "Generate a PPT from a prompt or outline" - "Create a deck in DaoCloud style / company brand style" - "Render PPT from structured block/xml with template consistency" ## Inputs - `title`: optional deck title fallback - `output_filename`: output pptx filename - `template_file`: optional template filename in skill directory - `block_xml`: block/xml payload (required) - `render_strategy`: `template_first` | `template_only` - `allow_html_fallback`: allow html/richtext block fallback to template content slides ## Output - `output_path`: absolute path to generated pptx - `slide_count`: number of slides generated - `message`: status message ## Notes - Requires `python-pptx`. - Uses local `PPT_Template.pptx` in skill directory by default. - Use `assets/demo_blocks.xml` for a full XML demo (toc + matrix + pie/bar/line + table + slogan).


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: sora-mury/karpathy-query-feedback (version 1.0.0)

# Karpathy Query → Wiki 回流 Skill ## 描述 实现 Karpathy LLM Knowledge Base 的第一阶段：Query → Wiki回流。 当用户发起查询时： 1. 使用 M-Flow 搜索相关记忆 2. 将结果格式化为 wiki 条目 3. 存入 wiki 层供后续 Compile 使用 ## 激活条件 - 用户发起知识查询 - 需要将查询结果回流到 wiki - session → knowledge pipeline ## 工作流 ``` 用户查询 → M-Flow搜索 → Wiki格式化 → 存入wiki层 → 供Compile使用 ``` ## Wiki 条目格式 ```markdown | source | content | tags | timestamp | |--------|---------|------|-----------| | session:xxx | 知识内容 | tag1,tag2 | 2026-04-05 | ``` ## 使用方式 ### Python API ```python from karpathy_query_feedback import QueryFeedbackPipeline pipeline = QueryFeedbackPipeline() results = await pipeline.query("用户询问的问题") wiki_entries = pipeline.format_as_wiki(results) await pipeline.save_to_wiki(wiki_entries) ``` ### 命令行 ```bash python scripts/query_and_save.py "查询内容" --format wiki --output ./wiki/ ``` ## 搜索模式 - `lexical`: BM25 全文搜索（快速、精确） - `episodic`: 向量搜索（语义相似） - `triplet`: 三元组搜索（关系推理） - `hybrid`: 混合搜索（lexical + episodic） ## 配置 - 使用 M-Flow 作为底层记忆系统 - Wiki 存储路径: `knowledge/wiki/` - 标签体系: 从配置或自动提取 ## 依赖 - m-flow-memory skill (已安装) - knowledge-distillation skill (用于标签提取) ## 文件结构 ``` karpathy-query-feedback/ ├── SKILL.md ├── scripts/ │ ├── __init__.py │ ├── pipeline.py # 核心管道 │ ├── formatter.py # Wiki格式化 │ ├── search.py # 搜索封装 │ └── query_and_save.py # CLI入口 └── docs/ └── README.md ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: yang1002378395-cmyk/openclaw-wechat-mp-guide (version 1.0.1)

--- name: openclaw-wechat-mp-guide version: 1.0.0 description: 微信公众号接入指南 - OpenClaw 连接公众号完整教程。适合：自媒体运营、内容创作者。 metadata: openclaw: emoji: "📱" requires: bins: [] --- # 微信公众号接入指南 让 AI 助手连接微信公众号，自动回复用户消息。 ## 前置条件 1. 微信公众号（服务号或订阅号） 2. OpenClaw 已安装 3. 公网服务器（80/443 端口） ## 步骤 1：获取公众号凭证 1. 登录 [微信公众平台](https://mp.weixin.qq.com) 2. 进入「开发」→「基本配置」 3. 记录以下信息： ``` AppID：wxxxxxxxxxxx AppSecret：xxxxxxxxxxxxxxxxxxxxxxxx ``` ## 步骤 2：配置服务器 1. 进入「基本配置」→「服务器配置」 2. 填写： - URL：`https://your-server.com/wechat` - Token：自定义（如 `openclaw2024`） - EncodingAESKey：随机生成 - 消息加解密方式：安全模式 ## 步骤 3：配置 OpenClaw ```bash # 设置微信连接 openclaw connect wechat # 输入凭证 AppID: wxxxxxxxxxxx AppSecret: xxxxxxxxxxxxxxxxxxxxxxxx [REDACTED_SECRET] EncodingAESKey: xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx # 启动服务 openclaw start ``` ## 步骤 4：验证连接 在公众号后台点击「提交」，系统会验证服务器配置。 成功后，用户发消息给公众号，AI 会自动回复。 ## 功能说明 ### 自动回复 用户发送任何消息，AI 根据内容智能回复。 ### 关键词触发 ```yaml # ~/.openclaw/config.yaml wechat: keywords: "帮助": "我是 AI 助手，可以回答你的问题..." "价格": "请查看我们的价格表..." ``` ### 菜单配置 通过公众号后台设置自定义菜单，点击后触发 AI 对话。 ## 高级功能 ### 多客服转接 ```yaml wechat: transfer_keywords: - "人工" - "客服" transfer_message: "正在转接人工客服，请稍候..." ``` ### 消息统计 ```bash # 查看消息统计 openclaw stats wechat ``` ### 敏感词过滤 ```yaml wechat: sensitive_words: - "违禁词1" - "违禁词2" filter_action: "replace" # 或 "block" ``` ## 常见问题 ### Q: 服务器配置提交失败？ 检查： 1. URL 是否可访问 2. Token 是否一致 3. 服务器是否启动 ### Q: 消息无响应？ 检查日志： ```bash openclaw logs -f | grep wechat ``` ### Q: 如何处理图片消息？ 需要开通「接收图片消息」权限，AI 可以识别图片内容并回复。 ## 定价参考 - 公众号接入：¥199 - 高级配置：¥499 - 企业定制：¥1999 ## 需要帮助？ 联系：微信 yang1002378395 或 Telegram @yangster151 --- **提示**：订阅号接口受限较多，建议使用服务号获得完整功能。

path: skill.json
content: {
  "name": "openclaw-wechat-mp-guide",
  "version": "1.0.0",
  "description": "微信公众号接入指南 - OpenClaw连接公众号完整教程",
  "author": "yang1002378395-cmyk",
  "license": "MIT",
  "keywords": ["wechat", "微信", "公众号", "openclaw", "自媒体", "运营"]
}


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: josephsuo/super-blueauto (version 0.1.0)

# SuperBlueAuto Universal Bluetooth AI Agent • Cross-Platform Bluetooth Control Hub One Skill. One AI. Control All Bluetooth Devices. --- ## Introduction SuperBlueAuto is a **cross-platform, AI-native, local-first** intelligent control hub for Bluetooth devices. One single skill supports all major operating systems: - Windows - macOS - Android - iOS / iPhone - HarmonyOS - Linux - Embedded Devices Control any Bluetooth / BLE device with natural language, regardless of brand or system. Supports lights, sockets, sensors, wearables, speakers, locks, health devices, remotes, and all BLE-compliant hardware. **All operations run locally. No cloud uploads. No data collection.** --- ## Platform Support ✅ Windows ✅ macOS ✅ Android ✅ iOS ✅ HarmonyOS ✅ Linux ✅ Embedded / Development Boards --- ## Core Capabilities - Scan nearby Bluetooth / BLE devices - Connect, disconnect, and monitor device status - Read device information: name, MAC, battery, signal, services - Read/write Bluetooth characteristics and serial communication - Batch management for multiple devices - Custom device adaptation rules --- ## Natural Language Examples - Scan for nearby Bluetooth devices - Connect to my Bluetooth light / socket / sensor - Read device battery level and signal strength - Turn on / off the Bluetooth device - Disconnect all Bluetooth devices in batch --- ## Permission Statement - Only accesses local system Bluetooth APIs - No mandatory network permissions - No device data upload - No privacy collection - No remote control without explicit user consent --- ## Version v1.0.0 – Initial Cross-Platform Framework Release --- ## Positioning The first truly cross-system, cross-brand, full-platform Bluetooth AI skill on ClawHub.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: charmmm718/quiver-ai (version 1.0.1)

--- name: quiver-ai description: | AI-native SVG vector graphics generation tool. Use when generating SVG graphics from text prompts or converting images to SVG. Supports: (1) Text-to-SVG generation with optional reference images, (2) Image-to-SVG conversion, (3) Real-time streaming rendering, (4) Multiple export formats (SVG, PNG, JPEG, WebP). Perfect for logos, illustrations, typography, and animations. --- # QuiverAI Skill QuiverAI is an AI-native vector graphics generation platform that creates high-quality SVG graphics from text prompts and reference images. ## Getting Started ### Web Interface 1. Visit https://app.quiver.ai/creations 2. Sign in or create an account 3. Enter a text prompt describing the desired graphic 4. Optionally upload reference images 5. Generate and download SVG ### API Usage For programmatic access, see [API Reference](references/api.md). ## Pricing Tiers | Tier | Price | Weekly SVGs | Features | |------|-------|------------|----------| | Free | $0 | 20 | Basic SVG export | | Basic | $20/mo | 100 | All export formats, Email support | | Pro | $40/mo | 250 | Priority support | | Enterprise | Custom | Custom | SSO, Custom training, On-premise | ## Use Cases - **Logos**: Brand identity and icons - **Illustrations**: Custom artwork and graphics - **Typography**: Text-based vector designs - **Animations**: Animated SVG graphics ## Tips - Be specific in prompts for better results - Use reference images to guide style - Check streaming for real-time progress


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: wondershare-boop/mediaio-hailuo-video-generator (version 1.0.0)

````skill --- name: mediaio-hailuo-video-generator description: "Generate AI videos using MiniMax Hailuo (Hailuo 2.3) via Media.io OpenAPI. Supports text-to-video and image-to-video with fast generation, high-quality HD output." metadata: {"mediaio": {"emoji": "", "requires": {"env": ["API_KEY"]}, "priority": "P0", "core_goal_keywords": ["text-to-video", "image-to-video"], "trigger_keywords": ["Hailuo", "Hailuo AI", "Hailuo video generator", "MiniMax Hailuo"]}, "publisher": "Community Maintainer", "source": "https://platform.media.io/docs/"} --- # Hailuo AI Video Generator ## Overview This skill focuses on a single model family and calls Media.io OpenAPI via `Skill.invoke(api_name, params, api_key)`. It includes only common APIs (`Credits`, `Task Result`) plus model-specific APIs for this skill. ## Core Trigger Keywords Hailuo, Hailuo AI, Hailuo video generator, MiniMax Hailuo ## Core Goal Keywords text-to-video, image-to-video ## Environment Variable - `API_KEY` (required): Media.io OpenAPI key used as `X-API-KEY`. ## Quick Start ```python import os from scripts.skill_router import Skill skill = Skill('scripts/c_api_doc_detail.json') [REDACTED_SECRET]'API_KEY', '') result = skill.invoke('Credits', {}, [REDACTED_SECRET]) print(result) ``` ## Available APIs - `Credits` (`user-credits`) - `Task Result` (`generation-result`) - `Hailuo 02` (`i2v-minimax-02`) - `Hailuo 2.3` (`i2v-minimax-v2-3`) ## Notes - Use exact `api_name` from `scripts/c_api_doc_detail.json` when invoking. - Generation APIs return `task_id`; poll with `Task Result`. ````


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: nexscope/amazon-rank-tracker (version 1.0.0)

--- name: amazon-rank-tracker description: "Track and analyze Amazon keyword rankings. Set up rank monitoring workflows, interpret ranking changes, and develop strategies to improve organic search position." metadata: nexscope: emoji: "📍" category: amazon --- # Amazon Rank Tracker 📍 Track and analyze Amazon keyword rankings. Set up rank monitoring workflows, interpret ranking changes, and develop strategies to improve organic search position. **Supported platforms:** Amazon, Shopify, WooCommerce, Walmart, TikTok Shop, Etsy, eBay, BigCommerce. Built by [Nexscope](https://www.nexscope.ai/) — your AI assistant for smarter e-commerce decisions. ## Install ```bash npx skills add nexscope-ai/eCommerce-Skills --skill amazon-rank-tracker -g ``` ## Usage ``` Track my rankings for these 10 keywords. My product is a stainless steel water bottle, currently on page 2 for my main keyword. Help me get to page 1. ``` ## Capabilities - Keyword rank tracking methodology and setup - Ranking factor analysis (relevance, velocity, conversion, reviews) - Rank change diagnosis (why did ranking go up or down?) - Keyword rank improvement strategy by priority - Rank tracking tool recommendations and comparison - Organic vs sponsored rank monitoring - BSR tracking and correlation with keyword rankings ## How This Skill Works **Step 1:** Collect information from the user's message — product, platform, current situation, and goals. **Step 2:** Ask one follow-up with all remaining questions using multiple-choice format. Allow shorthand answers (e.g., "1b 2c 3a"). **Step 3:** Research and analyze using the frameworks and methodology below. **Step 4:** Deliver structured, actionable output with specific recommendations, not vague advice. ## Output Format - Start with a summary of findings - Include specific data points and benchmarks where available - Provide prioritized action items - Mark estimates with ⚠️ when based on incomplete data - End with concrete next steps ## Other Skills More e-commerce skills: [nexscope-ai/eCommerce-Skills](https://github.com/nexscope-ai/eCommerce-Skills) Amazon-specific skills: [nexscope-ai/Amazon-Skills](https://github.com/nexscope-ai/Amazon-Skills) Built by [Nexscope](https://www.nexscope.ai/) — your AI assistant for smarter e-commerce decisions.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: wuxi304-collab/stainless-quote-generator (version 1.0.0)

# stainless-quote-generator - 不锈钢快速报价单生成器 ## 技能描述 为不锈钢销售场景快速生成专业报价单，含成本测算、运费计算、利润分析。 ## 核心功能 ### 1️⃣ 成本测算 ``` 成本 = 材料成本 + 加工费 + 运费 + 其他费用 材料成本 = 钢厂基价 + 材质差价 + 规格差价 + 表面差价 加工费 = 开平费 + 分条费 + 切割费 + 表面处理费 运费 = 干线运输 + 同城配送 + 装卸费 其他 = 包装费 + 保险费 + 资金成本 ``` ### 2️⃣ 价格数据库 - **钢厂基价**：太钢/宝新/张浦/青山主流牌号 - **材质差价**：304/316L/2205/2507 价差 - **规格差价**：不同厚度/宽度加价 - **表面差价**：2B/BA/No.1/拉丝/镜面 ### 3️⃣ 运费计算 - **干线运输**：按距离/重量/车型计算 - **同城配送**：无锡/佛山/天津等主要市场 - **快递小包**：样品快递费用 ### 4️⃣ 利润分析 - **毛利率**：(报价 - 成本) / 报价 - **吨钢利润**：元/吨 - **总利润**：元/单 - **底价提醒**：低于成本价时预警 ### 5️⃣ 报价单模板 支持多种格式： - **PDF**：正式报价单（盖章版） - **Excel**：可编辑版本 - **图片**：微信快速发送 - **飞书文档**：在线协作 ### 6️⃣ 报价历史 - **客户报价记录**：历史报价/成交价 - **价格趋势**：同一客户价格变化 - **竞品对比**：市场均价参考 ## 报价单模板 ### 标准报价单 ``` ═══════════════════════════════════════════════════════ 不锈钢材料报价单 ═══════════════════════════════════════════════════════ 报价单号：QT-20260326-001 报价日期：2026-03-26 有效期：7 天 客户信息： 名称：新乡七里营封头厂 联系人：张总 电话：138****1234 地址：河南省新乡市新乡县七里营镇 ─────────────────────────────────────────────────────── 产品明细： ─────────────────────────────────────────────────────── | 序号 | 材质 | 规格 | 表面 | 数量 | 单价 | 金额 | |------|------|------|------|------|------|------| | 1 | 304 | 2.0×1219×C | 2B | 5 吨 | ¥15,800 | ¥79,000 | | 2 | 304 | 3.0×1219×C | 2B | 3 吨 | ¥15,600 | ¥46,800 | | 3 | 316L | 2.0×1219×C | 2B | 2 吨 | ¥23,500 | ¥47,000 | ─────────────────────────────────────────────────────── 费用明细： ─────────────────────────────────────────────────────── 材料成本：¥158,000 加工费用：¥2,000 (开平) 运输费用：¥3,500 (无锡→新乡) 包装费用：¥500 (木托盘) ─────────────────────────────────────────────────────── 合计成本：¥164,000 报价金额：¥172,800 (含税含运) 毛利润：¥8,800 毛利率：5.1% ─────────────────────────────────────────────────────── 备注： 1. 以上价格为含税含运价 2. 交期：收到预付款后 10-15 天 3. 付款方式：30% 预付，发货前付清 4. 质量标准：GB/T 3280-2015 5. 质保期：质量问题 30 天内反馈 ═══════════════════════════════════════════════════════ 报价员：商务拓展专家 联系电话：XXX-XXXX-XXXX 电子邮箱：[REDACTED_SECRET] ═══════════════════════════════════════════════════════ ``` ## 使用示例 ```javascript // 生成报价单 const quote = await generator.createQuote({ 客户：{ 名称："新乡七里营封头厂", 联系人："张总", 电话："138****1234", 地址："河南省新乡市新乡县七里营镇" }, 产品：[ { 材质："304", 规格："2.0×1219×C", 表面："2B", 数量：5, 单位："吨" }, { 材质："316L", 规格："2.0×1219×C", 表面："2B", 数量：2, 单位："吨" } ], 发货地："无锡", 目的地："新乡", 毛利率目标：0.05 }); // 输出格式：pdf | excel | image | doc await quote.export('pdf'); ``` ## 价格更新 ### 自动更新 - **每日钢价**：抓取我的钢铁网/上海有色网 - **镍价联动**：LME 镍价实时追踪 - **运费调整**：物流平台价格同步 ### 手动调整 - **钢厂调价**：收到钢厂调价通知后手动更新 - **特殊规格**：非常规规格单独录入 - **大客户价**：协议客户特殊价格 ## 集成能力 - **微信发送**：报价单图片一键发送 - **邮件发送**：PDF 正式版邮件 - **飞书集成**：报价单同步到飞书文档 - **CRM 同步**：报价记录同步到客户档案 ## 版本历史 - **v1.0.0** (2026-03-26) - 初始版本 - 基础报价单生成 - 成本测算模型 - 运费计算模板 --- **作者**: 商务拓展专家 👔 **适用场景**: 不锈钢销售报价、成本核算、利润分析


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: lilianzhu/zadig (version 4.0.2)

--- name: zadig description: ⚠️ 需要 ZADIG_API_URL + ZADIG_API_KEY | Zadig DevOps 平台 API 客户端 --- # Zadig Skill 基于 Zadig OpenAPI 规范实现的 DevOps 平台客户端。 ## 配置 必须配置以下环境变量（添加到 ~/.openclaw/workspace/.env）： ```bash # 必填 ZADIG_API_URL=https://your-zadig.example.com ZADIG_API_KEY=your-jwt-token # 可选 ZADIG_DEFAULT_PROJECT=your-project ``` ## 权限说明 - read:env - 读取 .env 文件获取 API 凭证 - network:https - 向 Zadig API 服务器发起请求 ## 核心功能 - 项目管理 - 工作流管理 - 环境管理 - 服务管理 - 构建管理 - 测试管理 ## 使用示例 ```javascript const zadig = require('./skills/zadig'); // 列出项目 const { projects } = await zadig.listProjects(); // 触发工作流 await zadig.triggerWorkflow({ projectKey: 'yaml', workflowKey: 'build', inputs: [...] }); // ===== 便捷方法 ===== // 获取服务状态（一步到位） const status = await zadig.getServiceStatus({ projectKey: 'yaml', envName: 'dev', serviceName: 'service1' }); /* 返回: { service_name: 'service1', env_name: 'dev', status: 'Running', image: 'koderover.tencentcloudcr.com/test/service1:xxx', pod_name: 'service1-xxx-xxx', node: '172.16.64.16', ip: '172.16.64.132', ports: [{ containerPort: 20221, protocol: 'TCP' }], service_endpoints: [{ name: 'service1', service_port: 20221, node_port: 31331 }] } */ // 获取服务日志（同步返回文本） const logs = await zadig.getServiceLogsSync({ projectKey: 'yaml', envName: 'dev', serviceName: 'service1', tailLines: 100 }); // 返回日志文本 // 获取工作流任务状态 const task = await zadig.getWorkflowTask({ workflowKey: 'dev-build', taskId: 67 }); ``` ## 安全建议 1. 使用最小权限的 API Token 2. 不要将 API Key 提交到版本控制


Security scan verdicts — ClawScan: suspicious | static analysis: suspicious | VirusTotal: suspicious | SkillSpector: suspicious (CRITICAL)