OpenClaw/clawhub-security-signals huggingface dataset:
Skill: fangbb-coder/session-compactor (version 1.0.0)

--- name: session-compactor description: 自动会话压缩以优化 token 使用。当会话消息数超过阈值时，将早期历史压缩为结构化摘要，保留工具调用和关键事实。适用于长对话场景以节省上下文窗口。核心算法参考 claw-code 项目的 compact.rs 设计。 metadata: { "clawdbot": { "emoji": "🗜️", "requires": { "bins": ["node"] }, "tools": [ { "name": "compact_session", "description": "压缩当前会话历史以节省 tokens。自动检测 token 数，将早期消息替换为摘要", "inputSchema": { "type": "object", "properties": { "maxTokens": { "type": "number", "description": "触发压缩的 token 阈值 (默认从配置读取)" }, "minMessagesToKeep": { "type": "number", "description": "最少保留的最新消息数 (默认 5)" }, "force": { "type": "boolean", "description": "是否强制压缩 (即使未超阈值)" } } } } ] } } --- # Session Compactor 本技能提供自动化的会话压缩功能，解决长对话导致的 token 超限问题。 ## 何时使用 - 会话消息数超过 30 条，接近模型上下文窗口限制 - 需要保留关键上下文但控制 token 消耗 - 手动调用以优化对话历史 ## 快速开始 ### 配置 在 `openclaw.config.json` 中启用: ```json { "skills": { "session-compactor": { "enabled": true, "maxTokens": 3000, "minMessagesToKeep": 5, "autoCompact": true } } } ``` ### 自动模式 设置 `"autoCompact": true` 后，每次会话更新会自动检测并压缩。 ### 手动调用 调用工具 `compact_session`: ```bash openclaw tools call compact_session '{"force": false}' ``` ## 工作原理 1. **Token 估算** - 使用启发式方法 (1 token ≈ 4 字符) 2. **触发检测** - 当前 tokens > maxTokens? 3. **选择目标** - 保留最新 `max(minKeep, total/3)` 条消息 4. **生成摘要** - 提取对话目标、工具调用、关键事实 5. **替换** - 用单条系统消息替代所有早期消息 压缩 **不可逆**，早期消息细节会丢失。 ## 配置参数 | 参数 | 类型 | 默认 | 说明 | |------|------|------|------| | `maxTokens` | number | 3000 | 触发压缩的 token 阈值 | | `minMessagesToKeep` | number | 5 | 至少保留的最新消息数 | | `autoCompact` | boolean | true | 启用自动压缩 | | `force` (工具参数) | boolean | false | 强制压缩（调用时） | ## 示例 ### 压缩前 ```json [ {"role":"user","content":"请分析赛力斯2025年报"}, {"role":"assistant","content":"[tavily_search] 正在搜索..."}, {"role":"user","content":"还要2024年对比数据"}, {"role":"assistant","content":"[tavily_search] 已找到..."} // ... 继续累积到 50+ 条 ] ``` ### 压缩后 ```json [ {"role":"system","content":"## 会话摘要 (已压缩早期 45 条消息)\n- 对话目标: 分析赛力斯2025年报...\n- 工具调用: 6 次..."}, {"role":"user","content":"那么深信服的2025预测呢？"}, {"role":"assistant","content":"继续..."} // ... 最新 16 条保持完整 ] ``` ## 技术实现 核心算法实现于 `scripts/compact_session.js`: ```javascript const { compactSession } = require('./scripts/compact_session'); const result = await compactSession(messages, { maxTokens: 4000, force: false }); console.log(result.compacteded); // true/false console.log(result.savedTokens); // 节省的 token 数 ``` 详细设计文档见 `references/architecture.md`。 ## 注意事项 ⚠️ **压缩不可逆** - 早期消息细节永久丢失 ⚠️ **阈值设置** - 建议 maxTokens 设较高 (4000-6000) 避免过早压缩 ⚠️ **生产增强** - 考虑集成 LLM 生成高质量摘要 ## 参考资料 - `references/architecture.md` - 详细设计说明 - claw-code 原始实现: `compact.rs` (https://github.com/instructkr/claw-code) --- **版本**: 0.1.0 **作者**: 小李 (基于 claw-code 分析实现)


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: mars82311111/mars-weather-ai (version 1.0.0)

--- name: weather description: Get current weather and forecasts (no API key required). homepage: https://wttr.in/:help metadata: {"clawdbot":{"emoji":"🌤️","requires":{"bins":["curl"]}}} --- # Weather Two free services, no API keys needed. ## wttr.in (primary) Quick one-liner: ```bash curl -s "wttr.in/London?format=3" # Output: London: ⛅️ +8°C ``` Compact format: ```bash curl -s "wttr.in/London?format=%l:+%c+%t+%h+%w" # Output: London: ⛅️ +8°C 71% ↙5km/h ``` Full forecast: ```bash curl -s "wttr.in/London?T" ``` Format codes: `%c` condition · `%t` temp · `%h` humidity · `%w` wind · `%l` location · `%m` moon Tips: - URL-encode spaces: `wttr.in/New+York` - Airport codes: `wttr.in/JFK` - Units: `?m` (metric) `?u` (USCS) - Today only: `?1` · Current only: `?0` - PNG: `curl -s "wttr.in/Berlin.png" -o /tmp/weather.png` ## Open-Meteo (fallback, JSON) Free, no key, good for programmatic use: ```bash curl -s "https://api.open-meteo.com/v1/forecast?latitude=51.5&longitude=-0.12&current_weather=true" ``` Find coordinates for a city, then query. Returns JSON with temp, windspeed, weathercode. Docs: https://open-meteo.com/en/docs

path: _meta.json
content: ownerId: kn70pywhg0fyz996kpa8xj89s57yhv26
slug: weather
version: 1.0.0
publishedAt: 1767545394459

Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: pupuking723/internal-comms-anthropic (version 1.0.0)

--- name: internal-comms description: A set of resources to help me write all kinds of internal communications, using the formats that my company likes to use. Claude should use this skill whenever asked to write some sort of internal communications (status reports, leadership updates, 3P updates, company newsletters, FAQs, incident reports, project updates, etc.). license: Complete terms in LICENSE.txt --- ## When to use this skill To write internal communications, use this skill for: - 3P updates (Progress, Plans, Problems) - Company newsletters - FAQ responses - Status reports - Leadership updates - Project updates - Incident reports ## How to use this skill To write any internal communication: 1. **Identify the communication type** from the request 2. **Load the appropriate guideline file** from the `examples/` directory: - `examples/3p-updates.md` - For Progress/Plans/Problems team updates - `examples/company-newsletter.md` - For company-wide newsletters - `examples/faq-answers.md` - For answering frequently asked questions - `examples/general-comms.md` - For anything else that doesn't explicitly match one of the above 3. **Follow the specific instructions** in that file for formatting, tone, and content gathering If the communication type doesn't match any existing guideline, ask for clarification or more context about the desired format. ## Keywords 3P updates, company newsletter, company comms, weekly update, faqs, common questions, updates, internal comms

path: examples/general-comms.md
content:   ## Instructions
  You are being asked to write internal company communication that doesn't fit into the standard formats (3P
  updates, newsletters, or FAQs).

  Before proceeding:
  1. Ask the user about their target audience
  2. Understand the communication's purpose
  3. Clarify the desired tone (formal, casual, urgent, informational)
  4. Confirm any specific formatting requirements

  Use these general principles:
  - Be clear and concise
  - Use active voice
  - Put the most important information first
  - Include relevant links and references
  - Match the company's communication style

Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: zhangyang-1/jpbot-device-skill (version 1.0.4)

Skill 描述 当用户查询金彭智能三轮车的车辆信息（车辆详情、车辆上下电状态、车辆实时状态、车辆位置、车辆剩余电量、车辆骑行里程、车辆骑行轨迹）时使用。 适用场景 读取设备状态、电池信息、行驶数据 配置车辆参数（速度限制、灯语等） 排查常见故障 导出骑行统计数据 功能概览 功能 描述 设备连接 连接 金彭设备 状态查询 获取电池、里程、固件版本等信息 参数配置 修改速度限制、灯效等设置 故障诊断 分析错误码并提供解决方案 固定输出 该 skill 目前仅做提示，统一回复： 该skill正在测试中，敬请期待。


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: oct16/tickhub (version 0.0.1)

--- name: stock-query description: | 股票实时行情查询技能。支持A股、港股、美股个股的实时价格、涨跌幅、成交量查询。 Use when: 用户询问某只股票的"股价"、"行情"、"涨了没"、"多少钱了"。 NOT for: 历史K线分析、技术指标计算、投资建议推荐。 --- # 股票查询助手 ## 概述 根据用户提供的股票代码或名称，通过东方财富/新浪财经API获取该股票的实时行情数据，返回当前价格、涨跌幅、成交量等核心指标。适用于快速查看股价、判断涨跌场景。 ## 工作流程 1. 从用户消息中提取股票标识（代码优先，其次是名称） 2. 判断市场：6位数字且60/00/30开头 → A股；数字.HK → 港股；字母组合 → 美股 3. 调用对应市场的实时行情API 4. 解析返回的JSON数据 5. 格式化为易读文本输出 ## API 调用示例 ### A股行情接口 ```bash # 获取贵州茅台（600519）实时行情 curl "https://tickhub.net/stock/600519"


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: teingi/install-powermem-memory-minimal (version 0.1.0)

--- name: install-powermem-memory-minimal description: memory-powermem 最小安装步骤（OpenClaw + PowerMem 长期记忆），面向个人用户；无需单独配置 powermem.env，复用 OpenClaw 里已配好的对话模型。本 skill 可独立分发，不依赖其他安装类 skill。 triggers: - "PowerMem 快速安装" - "PowerMem 最简单安装" - "memory-powermem 最小安装" - "怎么装 PowerMem 记忆" - "OpenClaw 记忆 怎么装" - "安装长期记忆" - "Quick install PowerMem" - "PowerMem quickstart" - "Easiest PowerMem setup" - "Minimal install memory-powermem" - "Install powermem memory minimal" --- # PowerMem 记忆 · 极简安装（个人用户） 你只要记住几件事：**OpenClaw 能正常聊天**、**Python 先确认 ≥ 3.10**、**本机装好 PowerMem**、**装上插件**。不用手写 `powermem.env`，记忆用的模型和 Key 会跟你在 OpenClaw 里配的一样。 --- ## 你要做什么（按顺序） 1. **确认 OpenClaw 已经能用** 终端执行 `openclaw --version`，并且你已经在 OpenClaw 里配好了**平时对话用的模型**（能正常回复即可）。 2. **先检查 Python 版本（必须 ≥ 3.10）** 在创建虚拟环境或执行 `pip install` **之前**必须先确认版本，否则后续容易装失败或运行异常： ```bash python3 --version ``` 输出应为 **Python 3.10.x、3.11.x、3.12.x** 等（次版本号 ≥ 10）。也可用下面命令做一次硬性校验（不通过会报错退出）： ```bash python3 -c "import sys; assert sys.version_info >= (3, 10), '需要 Python 3.10 或更高'; print(sys.version.split()[0], 'OK')" ``` 若版本不够：先升级本机 Python，或安装并使用 `python3.11` / `python3.12` 等满足要求的解释器，并将下面步骤里的 **`python3`** 换成实际命令（例如 `python3.12 -m venv ...`）。 3. **安装 PowerMem（Python）** 建议用虚拟环境，然后安装： ```bash python3 -m venv ~/.openclaw/powermem/.venv source ~/.openclaw/powermem/.venv/bin/activate pip install powermem ``` 装好后执行 `pmem --version`，能输出版本就行。 4. **让网关能找到 `pmem`** 如果你启动 `openclaw gateway` 的终端**没有**激活上面的 venv，有两种简单办法二选一： - 每次开网关前先 `source ~/.openclaw/powermem/.venv/bin/activate`；或 - 在插件配置里把 **`pmemPath`** 写成 venv 里 `pmem` 的**完整路径**（装完后可用 `which pmem` 查看）。 5. **一键装插件（推荐）** 在 **Mac / Linux** 上执行（需已安装 OpenClaw）： ```bash curl -fsSL https://raw.githubusercontent.com/ob-labs/memory-powermem/main/install.sh | bash -s -y ``` 脚本会把插件放进 OpenClaw，并打开「用 OpenClaw 的模型驱动记忆」等默认选项。 6. **重启网关并检查** ```bash openclaw gateway ``` 另开终端，**先**确认插件已被网关加载： ```bash openclaw plugins list ``` 输出里要有 **memory-powermem**，且其状态为 **loaded**（已加载）。若只有安装记录、状态不是 loaded，先按下面「若某一步失败」处理，**不要**跳过这步直接去测 `ltm`。 通过后再检查记忆健康并试写读： ```bash openclaw ltm health ``` 显示健康后试一句： ```bash openclaw ltm add "我喜欢喝美式" openclaw ltm search "咖啡" ``` --- ## 若某一步失败 | 情况 | 怎么办 | |------|--------| | `python3 --version` 低于 3.10 | **先升级或换用** `python3.11` / `python3.12` 等，再重做「检查 Python」与 venv 步骤；不要跳过版本检查强行 `pip install`。 | | `pip install powermem` 报错 | 再次确认 Python ≥ 3.10；换干净 venv 再试。 | | `pmem` 找不到 | 激活 venv，或配置 **`pmemPath`** 为绝对路径。 | | `plugins list` 没有 **memory-powermem**，或状态不是 **loaded** | 确认已执行安装脚本或 `openclaw plugins install`；`plugins.enabled` 为 true、`plugins.slots.memory` 为 **memory-powermem**；改完后**重启 gateway**，再执行 `openclaw plugins list` 复查。 | | `ltm health` 不健康 | 确认 OpenClaw 里**默认模型**和 API Key 本身能聊天；升级 OpenClaw 到较新版本后再试。 | | 想要更多选项（多实例、HTTP、自建服务器等） | 查阅 **[memory-powermem](https://github.com/ob-labs/memory-powermem)** 仓库根目录的 **INSTALL.md** 与 **README**。 | --- ## 说明（一句话） 记忆数据默认存在本机 OpenClaw 数据目录下的 SQLite 里；**不需要**你再单独维护一份 PowerMem 的 `.env`，除非你熟悉进阶配置。


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: paudyyin/summarize-cn (version 1.0.0)

--- name: summarize version: 1.0.0 description: 智能内容摘要工具，支持长文本、文档、网页内容自动摘要，提取核心要点、关键词，支持自定义摘要长度。 metadata: author: openclaw-community category: productivity capabilities: - 长文本智能摘要，保留核心信息 - 支持TXT/MD/PDF等常见文档摘要 - 网页内容自动抓取+摘要生成 - 提取核心关键词、关键短语 - 自定义摘要长度（短句/段落/详细） - 多语言支持（中文/英文） --- # Summarize 智能内容摘要工具 自动对各类内容进行结构化摘要，提炼核心信息，节省阅读时间。 ## 核心功能 ### 1. 文本摘要 直接输入长文本，自动生成结构化摘要： - 支持最多10万字长文本处理 - 自动提炼核心观点、关键结论 - 保留重要数据、时间、人物等关键信息 - 支持自定义摘要长度（简洁/标准/详细） ### 2. 文档摘要 支持本地常见文档直接摘要： - 支持格式：.txt/.md/.docx/.pdf - 自动提取内容，保留排版信息 - 生成文档大纲+核心内容摘要 ### 3. 网页摘要 输入URL自动抓取网页内容并生成摘要： - 自动过滤广告、导航栏等无效内容 - 提取正文核心信息 - 保留来源链接、发布时间等元信息 ### 4. 关键词提取 自动提取内容核心关键词、关键短语： - 关键词按重要程度排序 - 支持自定义关键词数量 - 自动识别专有名词、行业术语 ## 使用方法 ### 基础使用 ```powershell # 直接摘要文本 summarize "这里是需要摘要的长文本内容..." # 从文件读取内容摘要 summarize --file ./report.md # 网页内容摘要 summarize --url https://example.com/article # 提取关键词 summarize --keywords "文本内容" ``` ### 高级参数 | 参数 | 说明 | 默认值 | |------|------|--------| | --length | 摘要长度：short/medium/long | medium | | --output | 输出格式：text/markdown/json | text | | --keywords-count | 提取关键词数量 | 5 | | --include-meta | 是否包含元信息（字数、统计等） | false | ## 示例 ### 文本摘要 ```powershell summarize --length long "2026年AI行业发展报告全文..." ``` 输出： > 【摘要】2026年AI行业核心进展包括...主要趋势包括...面临的挑战包括... > 【关键词】AI大模型, 多模态, 推理成本, 智能体 ### 网页摘要 ```powershell summarize --url https://zhuanlan.zhihu.com/p/xxxxxxxxxx --output markdown ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: astonysh/docuclaw (version 0.1.0)

--- name: DocuClaw description: Sovereign document intelligence & archival system. Extracts structured data from invoices, receipts, and contracts 100% locally using AI. --- # DocuClaw Skill DocuClaw provides a sovereign data infrastructure for processing and archiving documents. It uses multimodal LLMs to extract structured information from scans, photos, and emails, storing everything in human-readable, version-controllable Markdown files. ## Use Cases - **Expense Management**: Extract totals, taxes, and dates from receipts for tax filing. - **Contract Analysis**: Monitor expiration dates and renewal clauses in legal documents. - **Sovereign Archival**: Maintain a local-first, GDPR/GoBD compliant archive of all physical and digital mail. - **Unified Querying**: Ask questions about your document history without cloud exposure. ## Key Features - **100% Local**: Zero cloud dependency. Your private data never leaves your hardware. - **Plug-and-Play Parsers**: Extensible architecture for country-specific document formats. - **AI-Powered**: Supports Ollama, OpenAI Vision, or any multimodal model for intelligent extraction. - **Markdown Schema**: Normalizes all documents into a universal schema with YAML metadata. ## Workflow Example 1. **Input**: A PDF invoice or a photo of a receipt. 2. **Process**: Run `docuclaw process` to trigger AI extraction. 3. **Archive**: Document is saved to your local vault as `YYYY/MM/filename.md`. 4. **Action**: The extracted data is synced to your calendar or accounting tool. ## Integration DocuClaw is designed to work seamlessly with the OpenClaw ecosystem, allowing AI agents to perform RAG (Retrieval-Augmented Generation) over your local document archive.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: aaiccee/med-record-gen (version 1.0.0)

--- name: med-initial-record-gen description: 从中文医患对话文本生成门诊初诊病历，输出结构化分段的病历正文（文本）。 metadata: { "openclaw": { "emoji": "📝" } } --- # 门诊初诊病历生成 概述 ---- 给定一份 **中文医患对话文本**（通常来自 ASR 转写），本技能生成一份门诊 **初诊病历** 文本，包含常见病历分段（如主诉、现病史、既往史、查体、辅助检查、诊断、处理等）。 常见输出分段： - 主诉 - 现病史 - 既往史 - 月经史（如适用） - 查体 - 辅助检查 - 诊断 - 处理 数据安全、隐私与伦理声明 ------------------------ - **最小必要原则**：仅处理生成病历所必需的对话内容；不要求也不鼓励包含姓名、证件号、手机号、详细地址等身份信息。 - **严格脱敏**：在发送至任何模型/接口前，会对可识别个人身份的信息进行脱敏/去标识化处理（如姓名、证件号、手机号、详细地址、人脸/影像等）。仅传递脱敏后的必要信息用于本次 skill 调用。 - **不做本地持久化**：不将用户输入与中间结果写入本地持久化存储（包含磁盘文件、数据库、日志）。仅在内存中短暂处理；**本次调用结束即销毁**。 - **第三方 API 风险提示**：在功能需要时，可能会调用第三方模型/服务接口；此时仅会发送**脱敏后的必要信息**，并使用加密传输。除完成本次请求外，不用于任何其他用途（如训练、画像、营销）。 - **医疗边界**：本技能用于病历文本整理与结构化表达的辅助生成，不构成医疗诊断或治疗建议；请由执业医生复核并承担最终医疗责任。 输入格式 -------- 纯文本对话（UTF-8），建议一行一句/一轮，例如： 患者：…… 医生：…… 患者：…… 医生：…… 快速开始 -------- ```bash # 从 skills 目录运行 python3 scripts/gen_initial_record.py \ --input data/med-initial-record-gen/dialogue.txt ``` 参数说明 -------- * `--input PATH` - 输入对话文本路径（UTF-8）。 * `--output PATH` - 输出病历路径（默认：`../runs/med-initial-record-gen/record.txt`）。 * `--diag-id STRING` - 对话 ID（默认：`skill-diag`）。 * `--timeout SECONDS` - 超时秒数；`0` 表示一直等待（默认：0）。 输出约定 -------- - 若输出路径父目录不存在，会自动创建。 - 输出为 UTF-8 文本，包含常见门诊初诊病历分段。 测试命令 -------- 从 `skills` 目录执行（网络自测）： ```bash python3 self_tests/med-initial-record-gen/self_test_initial_record_gen.py --run-network ```

path: _meta.json
content: ownerId: kn76wejkeqxfc03j0rfxp2jaj982m7aa
slug: med-initial-record-gen
version: 1.0.0
publishedAt: 1773287610243

Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: shuowang-ai/knowair-historical (version 1.0.0)

--- name: knowair-historical description: Get historical weather data up to 72 hours back via the Caiyun Weather API. Returns past temperature, weather conditions, precipitation, wind, humidity, apparent temperature, and air quality at regular intervals. Use when the user asks about past weather, yesterday's weather, what was the temperature earlier, recent weather history, or weather data from the past few hours/days. license: MIT-0 compatibility: Requires python3 and internet access. argument-hint: "For example: what was the weather yesterday at 116.3176,39.9760, or past 24 hours in Shanghai" allowed-tools: ["Bash(python3:*)", "Read"] metadata: openclaw: emoji: "📜" primaryEnv: CAIYUN_TOKEN requires: env: - CAIYUN_TOKEN bins: - python3 --- # KnowAir Historical — Past Weather Data Query historical weather data for up to 72 hours back using the Caiyun Weather API. ## Prerequisites 1. A valid Caiyun Weather API token set as `CAIYUN_TOKEN` environment variable, or stored in `~/.config/knowair/token`. 2. Coordinates (longitude, latitude) for the target location. ## Quick Start ```bash python3 scripts/query_historical.py --lng 116.3176 --lat 39.9760 --hours 24 ``` ## Workflow 1. **Resolve coordinates** — convert city name to coordinates if needed. 2. **Run the script**: ```bash python3 scripts/query_historical.py --lng <LNG> --lat <LAT> --hours <HOURS> ``` 3. **Present results** — summarize temperature range, weather changes, and notable events in the past period. ### Options | Flag | Description | Default | |------|-------------|---------| | `--lng` | Longitude (-180 to 180) | Required | | `--lat` | Latitude (-90 to 90) | Required | | `--hours` | Hours to look back (1-72) | `24` | | `--lang` | Output language: `en` or `zh` | `en` | ## Defaults - Hours back: 24 - Language: `en` ## Failure Handling - Missing token → exit code 2 with setup instructions. - API error → exit code 1 with error details.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: cyffeifeifei/prana-cyf-20260327 (version 1.0.1)

--- name: 市场实时快讯 description: 7x24小时财经新闻实时爬取与展示。支持金十数据等多个财经新闻源的实时爬取，通过WebSocket实现秒级推送，提供美观的前端界面展示最新财经资讯。适用于需要实时监控财经动态的场景。 --- 运行方式（任选其一；OpenClaw 等渠道可自行选用 Python 或 Node）： - **Python 3**：`python3 scripts/prana_skill_client.py -m "…" [-t thread_id] [-b base_url]` - **Node.js 18+**：先在包根目录执行 **`npm install`**，再执行 `node scripts/prana_skill_client.js -m "…" [-t thread_id] [-b base_url]` ## 运行与结果展示约定 集成方在运行本封装技能时：对 **`/api/claw/agent-run`** 与 **`/api/claw/agent-result`** 返回的内容须**直接**交给最终用户（原样展示或原样传递），**不要**另行改写、摘要、拼接或做其它二次处理。薄客户端仅负责请求上述接口及必要的 `agent-result` 轮询，标准输出即为服务端 JSON。


Security scan verdicts — ClawScan: suspicious | static analysis: suspicious | VirusTotal: suspicious | SkillSpector: suspicious (CRITICAL)
Skill: up2itnow/agentpay-mcp (version 1.0.0)

--- name: agentpay-mcp description: MCP server that gives AI agents the ability to make payments, manage budgets, and handle billing -- directly from Claude Desktop, Cursor, Cline, or any MCP-compatible agent runtime. version: 1.0.0 author: up2itnow tags: - mcp - payments - crypto - usdc - ai-agents - billing - autonomous-trading - polygon metadata: openclaw: requires: bins: - node env: - AGENT_PRIVATE_KEY - RPC_URL --- # AgentPay MCP Payment layer for AI agents via Model Context Protocol. AgentPay MCP gives your AI agent the ability to make payments, track spending, and manage payment channels -- without leaving the agent runtime. Works with Claude Desktop, Cursor, Cline, Windsurf, and any MCP-compatible environment. ## What It Does - **Make payments:** Send USDC on Polygon directly from agent tool calls - **Budget management:** Hard spending limits enforced per-session and per-day - **Payment channels:** Open Handshake58-style channels for sub-cent micropayments - **CCTP bridge:** Cross-chain USDC settlement (Ethereum, Base, Polygon, Arbitrum) - **Non-custodial:** Agent holds its own keys -- no third-party custody ## Installation ```bash npm install -g agentpay-mcp ``` Add to your MCP config (`~/.config/claude/mcp.json` or equivalent): ```json { "mcpServers": { "agentpay": { "command": "agentpay-mcp", "env": { "AGENT_PRIVATE_KEY": "0x...", "RPC_URL": "https://polygon-rpc.com", "MAX_TX_USDC": "25", "MAX_DAILY_USDC": "500" } } } } ``` ## Tools Exposed | Tool | Description | |---|---| | `pay` | Send USDC to an address (enforces spend limits) | | `check_balance` | Query agent wallet balance | | `get_spending` | Current session and daily spend totals | | `open_channel` | Open a micropayment channel (Handshake58 compatible) | | `pay_channel` | Issue a signed payment voucher (zero gas) | | `close_channel` | Settle and reclaim unused channel funds | | `bridge_usdc` | Cross-chain USDC via CCTP | ## Usage Example In Claude Desktop with AgentPay MCP configured: > "Pay 5 USDC to 0xABC...123 for the API call results" The agent calls `pay(to="0xABC...123", amount=5, token="USDC")`. If within limits, it executes immediately. If over limits, it returns a request for human approval. ## Environment Variables | Variable | Required | Description | |---|---|---| | `AGENT_PRIVATE_KEY` | Yes | Agent's signing key (0x-prefixed) | | `RPC_URL` | Yes | Polygon JSON-RPC endpoint | | `MAX_TX_USDC` | No | Per-transaction limit in USDC (default: 25) | | `MAX_DAILY_USDC` | No | Daily spending limit in USDC (default: 500) | ## GitHub https://github.com/AI-Agent-Economy/agentpay-mcp ## License MIT


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: brucegutman/pipeworx-archive (version 1.0.0)

--- name: pipeworx-archive description: Archive MCP — wraps the Internet Archive APIs (free, no auth) version: 1.0.0 metadata: openclaw: requires: bins: - curl emoji: "⚡" homepage: https://pipeworx.io/packs/archive --- # Pipeworx archive Archive MCP — wraps the Internet Archive APIs (free, no auth) Free, no API key required. Part of the [Pipeworx](https://pipeworx.io) open MCP gateway. ## When to Use Use this skill when the user asks about archive data or needs to query archive information. ## Available Tools ## How to Call The Pipeworx gateway speaks JSON-RPC 2.0 over HTTP POST. ### List available tools ```bash curl -s -X POST https://gateway.pipeworx.io/archive/mcp \ -H "Content-Type: application/json" \ -d '{"jsonrpc":"2.0","id":1,"method":"tools/list"}' ``` ### Call a tool ```bash curl -s -X POST https://gateway.pipeworx.io/archive/mcp \ -H "Content-Type: application/json" \ -d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"TOOL_NAME","arguments":{"param":"value"}}}' ``` ### MCP Client Config ```json { "mcpServers": { "pipeworx-archive": { "command": "npx", "args": ["-y", "mcp-remote@latest", "https://gateway.pipeworx.io/archive/mcp"] } } } ``` ## Notes - No authentication required - Free for all users - Rate limited for anonymous users (sign up at pipeworx.io for higher limits) - Returns JSON-RPC 2.0 responses


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