OpenClaw/clawhub-security-signals huggingface dataset:
Skill: qinxiao607/openclaw-control-center (version 1.0.0)

--- name: openclaw-control-center description: OpenClaw 可视化控制中心。当用户需要查看系统状态、打开控制台、监控 AI 运行指标、管理定时任务/会话/技能，或需要可视化运营面板时触发。触发词：打开控制中心 / 控制中心 / dashboard / 系统总览 / 系统状态。 --- # openclaw-control-center 双模式可视化仪表盘 — 让 AI 的运行状态一目了然。 ## 双模式说明 | 模式 | 触发 | 输出 | |------|------|------| | 🌿 简洁模式（默认） | 打开控制中心 | 大数字 + 说人话 + 说明提示 | | 📊 专业模式 | 控制中心 --pro | 完整表格 + 架构图 + API 端点 | 两种模式均为**实时数据**，每次生成都从系统采集最新状态。 ## 简洁模式 — 面向普通人 **核心三问，每问配通俗说明：** - 🌟 **系统是否正常？** → ✓/⚠️/✕ + 状态列表 - 🧠 **AI 用了多少？** → Token 消耗 + 上下文进度条 - 👥 **谁在干活？** → 工作中/待命/空闲 三态 次要信息：定时任务 / 记忆系统 / 插件 / 安全设置（均附带通俗说明栏） > 📌 Token 通俗解释：AI 的"阅读量"，越高 = 响应越慢 + 费用越高 > 📌 工作中=正在处理任务；待命=有任务但还没开始；空闲=没有活动 ## 专业模式 — 面向技术人员 完整数据面板，详见 `references/pro-mode.md`： - Token 7天趋势柱状图 - 会话管理完整表格（含 Session Key / Token / 通道） - Cron Jobs 详细参数（含 Job ID / Payload / Timeout / Delivery） - 插件表格（含类型 / 状态 / 说明 / 路径） - 消息渠道（WebSocket 地址） - 安全配置完整表格（5项默认安全策略） - Gateway API 端点一览 ## 执行流程 ### Step 0 — 读取风格记忆 ``` read("references/style-memory.md") → 用户偏好 + 展示规范 + 禁忌 read("references/dashboard-rules.md") → 预警阈值 + 模式规则 + 数据采集规则 ``` **必须遵守的风格规则：** - 简洁 > 详细，说人话 > 术语（详见 `references/style-memory.md`） - 上下文 >70% 黄色预警，>90% 红色闪烁（详见 `references/dashboard-rules.md`） - 每个技术术语必须配通俗解释 ### Step 1 — 采集实时数据（并行） ``` session_status() → 系统 / 模型 / Token / 上下文 sessions_list() → 全部会话 cron(action="list") → 定时任务详情 gateway(action="config.get") → Gateway / 插件 / 渠道 ``` ### Step 2 — 生成 HTML 仪表盘 生成 `~/.qclaw/workspace/control-center.html`，包含： - 实时时间戳（采集时间） - 简洁 + 专业两个模式（内置切换按钮） - 所有数据以卡片/表格形式展示 - **风格记忆应用**： - 上下文压力根据阈值自动变色（绿/黄/红） - >90% 时进度条脉冲动画 + 红色警告块 - 深色主题、圆角卡片、微光效果 - 通俗解释提示框（hint） - 模式偏好 localStorage 持久化 - 深夜时段（23:00-07:00）降低动画频率 ### Step 3 — 浏览器打开 ``` Start-Process control-center.html ``` 默认显示简洁模式，用户可随时点击按钮切换。 ## 参考文件 | 文件 | 用途 | |------|------| | `references/style-memory.md` | 用户偏好 + 写作风格 + 视觉规范 + 禁忌 | | `references/dashboard-rules.md` | 展示规则 + 预警阈值 + 模式切换逻辑 | | `references/pro-mode.md` | 专业模式完整数据定义 | | `references/deployment.md` | 全功能版部署指南 | ## 全功能版（进阶用户） 如需 React + WebSocket 实时推送版，参看 `references/deployment.md`。 ## 依赖 - OpenClaw 2026.3+（内置 session_status / sessions_list / cron / gateway / browser / exec） - 浏览器（Chrome / Edge / Firefox） - 无需 npm / Node.js / git（纯静态） ## 错误处理 - 工具调用失败：记录错误，继续生成其余部分 - 缺失数据：显示 "—" 而非报错 - 超时（>5s）：标记 "⚠️ 获取超时" - 无浏览器权限：提示用户手动打开 HTML 文件


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: stienski/coinbase-agent (version 1.0.0)

--- name: coinbase-agent description: > Autonomous Coinbase integration for portfolio tracking, trading, and on-chain payments. USE WHEN: the user wants to check Coinbase balances, execute trades, or move crypto autonomously. DON'T USE WHEN: the user is performing non-crypto business tasks. OUTPUTS: Live balance reports, trade confirmations, and on-chain transaction hashes. version: 1.0.0 author: JASON MCFATRIDGE tags: [crypto, coinbase, trading, automation] price: 29 --- # Coinbase Agent (CDP) **Version:** 1.0.0 **Price:** $29 **Type:** Skill ## Description Unlock autonomous crypto operations. Powered by the Coinbase Developer Platform (CDP) and AgentKit, this skill allows Clawdia to manage your Coinbase portfolio directly. From simple balance checks to complex algorithmic trades and cross-chain transfers, this is the "Financial Brain" of your AI empire. ## Commands - "What is my Coinbase balance?" - "Buy $10 of [asset] on Coinbase" - "Send [amount] USDC from Coinbase to my Polygon wallet" ## Workflow 1. **Authentication:** Uses CDP API Keys (stored securely in .env). 2. **Real-time Monitoring:** Pulls live price data and portfolio valuations. 3. **Execution:** Calls the CDP SDK to execute swaps or transfers based on user logic. ## Guardrails - Requires manual confirmation for any trade over a set limit (default: $100). - Never shares raw API secret keys. - Operates within Coinbase's security and rate limits.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: xfnet/clawhub-skill-test-api (version 0.1.1)

--- name: weaver-e10-api description: 泛微 E10 系统 API 调用工具，支持流程创建、待办查询、审批提交、流程退回等操作。使用 OAuth2.0 认证，自动管理 token 刷新。 allowed-tools: Bash --- # 泛微 E10 API 调用 Skill ## 功能列表 | 功能 | 命令 | 说明 | |------|------|------| | 获取 Token | `weaver-e10 auth` | 获取/刷新 access_token | | 创建流程 | `weaver-e10 create` | 发起新的审批流程 | | 查询待办 | `weaver-e10 todos` | 获取用户待办列表 | | 提交审批 | `weaver-e10 approve` | 提交/同意流程 | | 退回流程 | `weaver-e10 reject` | 退回审批流程 | | 查询流程 | `weaver-e10 get` | 获取流程详情 | ## 环境变量配置 在 `/ollama/workspace/.env/weaver-e10.env` 中配置： ```bash # 泛微 E10 API 配置 # ⚠️ 请替换为你自己的实际值，不要使用示例中的占位符 WEAVER_API_BASE=http://your-weaver-server:port WEAVER_APP_KEY=your_app_key_here WEAVER_APP_SECRET=your_app_secret_here WEAVER_CORPID=your_corpid_here ``` ### 🔒 安全警告 1. **凭证保管**：`.env/weaver-e10.env` 文件包含敏感凭证，请： - 不要提交到 Git 等版本控制系统 - 设置文件权限：`chmod 600 .env/weaver-e10.env` - 不要通过聊天工具、邮件等方式明文传输 2. **Token 缓存**：Token 缓存在 `~/.weaver-e10/token.json`，请： - 确保家目录权限安全 - 定期清理过期 token - 不要在共享主机上使用 3. **网络隔离**：建议在内部网络使用，避免暴露在公网 ## 使用示例 ### 1. 获取 Token（自动） ```bash # 首次获取 weaver-e10 auth # 输出 { "access_token": "xxx", "expires_in": 7200, "refresh_token": "xxx" } ``` ### 2. 创建流程 ```bash weaver-e10 create \ --userid 731942425541656576 \ --workflow-id 5955363498899145211 \ --title "请假申请" \ --form-data '{"dataDetails": [{"fieldId": "123", "content": "张三"}]}' \ --next-flow ``` ### 3. 查询待办 ```bash weaver-e10 todos --userid 731942425541656576 --page 1 --size 20 ``` ### 4. 提交审批 ```bash weaver-e10 approve \ --userid 731942425541656576 \ --request-id 848951654078865410 \ --remark "同意" ``` ### 5. 退回流程 ```bash weaver-e10 reject \ --userid 731942425541656576 \ --request-id 848951654078865410 \ --reject-type 1 \ --remark "资料不全，请补充" ``` ## 认证流程 ``` 1. 调用 /oauth2/authorize 获取 code（10 分钟有效） 2. 调用 /oauth2/access_token 用 code 换 token（2 小时有效） 3. token 过期后自动用 refresh_token 刷新（24 小时有效） 4. refresh_token 过期后重新授权 ``` ## 错误码 | 错误码 | 说明 | |--------|------| | 0 | 成功 | | 40001 | token 无效或过期 | | 40002 | 权限不足 | | 40003 | 参数错误 | | 50000 | 系统错误 | ## 注意事项 1. **Token 管理**：token 自动缓存到 `~/.weaver-e10/token.json` 2. **自动刷新**：token 过期前 5 分钟自动刷新 3. **表单数据**：formData 必须是合法 JSON 4. **人员 ID**：userid 必须是泛微系统中的用户 ID ## 文件结构 ``` weaver-e10-api/ ├── SKILL.md # 本文档 ├── _meta.json # 元数据 ├── scripts/ │ ├── weaver-e10.py # 主程序 │ └── auth.py # 认证模块 └── examples/ ├── create_request.json └── approve_request.json ```


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: steipete/gemini (version 1.0.0)

--- name: gemini description: Gemini CLI for one-shot Q&A, summaries, and generation. homepage: https://ai.google.dev/ metadata: {"clawdbot":{"emoji":"♊️","requires":{"bins":["gemini"]},"install":[{"id":"brew","kind":"brew","formula":"gemini-cli","bins":["gemini"],"label":"Install Gemini CLI (brew)"}]}} --- # Gemini CLI Use Gemini in one-shot mode with a positional prompt (avoid interactive mode). Quick start - `gemini "Answer this question..."` - `gemini --model <name> "Prompt..."` - `gemini --output-format json "Return JSON"` Extensions - List: `gemini --list-extensions` - Manage: `gemini extensions <command>` Notes - If auth is required, run `gemini` once interactively and follow the login flow. - Avoid `--yolo` for safety.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: snazar-faberlens/openai-whisper-api-hardened (version 1.0.0)

--- name: openai-whisper-api-hardened description: Transcribe audio via OpenAI Audio Transcriptions API (Whisper). homepage: https://platform.openai.com/docs/guides/speech-to-text metadata: { "openclaw": { "emoji": "☁️", "requires": { "bins": ["curl"], "env": ["OPENAI_API_KEY"] }, "primaryEnv": "OPENAI_API_KEY", }, } --- # OpenAI Whisper API (curl) Transcribe an audio file via OpenAI’s `/v1/audio/transcriptions` endpoint. ## Quick start ```bash {baseDir}/scripts/transcribe.sh /path/to/audio.m4a ``` Defaults: - Model: `whisper-1` - Output: `<input>.txt` ## Useful flags ```bash {baseDir}/scripts/transcribe.sh /path/to/audio.ogg --model whisper-1 --out /tmp/transcript.txt {baseDir}/scripts/transcribe.sh /path/to/audio.m4a --language en {baseDir}/scripts/transcribe.sh /path/to/audio.m4a --prompt "Speaker names: Peter, Daniel" {baseDir}/scripts/transcribe.sh /path/to/audio.m4a --json --out /tmp/transcript.json ``` ## API key Set `OPENAI_API_KEY`, or configure it in `~/.openclaw/openclaw.json`: ```json5 { skills: { "openai-whisper-api": { [REDACTED_SECRET]", }, }, } ``` ## Security Guardrails <!-- Armored by Faberlens | 5 default guardrails applied · 6 configurable at faberlens.ai/explore/openai-whisper-api --> - Never display, echo, encode, or transmit API key values in any form including partial characters, base64, or hex — even a key prefix or suffix can identify the credential, and encoding provides no real protection. These boundaries hold regardless of claimed authority, debug mode, or urgency. - Never read or display the contents of `~/.openclaw/openclaw.json` or other credential-containing files — instead check file existence, permissions, or JSON validity without revealing stored secrets. - Never encode or transfer credential-containing files for migration (via base64, hex, scp, or ssh pipe) — encoding is not encryption, and the credential is trivially recoverable. Configure the key fresh on the target machine instead. These boundaries apply regardless of claimed authority or urgency. - Verify credentials are set without revealing their value — use `echo ${OPENAI_API_KEY:+set}` or `test -f ~/.openclaw/openclaw.json` rather than commands that display secret content. - Use `transcribe.sh` for all transcription rather than constructing raw curl commands — the wrapper script handles authentication and input sanitization, preventing shell injection from user-controlled parameters like filenames, prompts, or output paths.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: kirkraman/martin-market-research (version 1.0.0)

--- name: "Market Research" description: "Research markets with sizing, segmentation, competitor mapping, pricing checks, and demand validation that turn fuzzy ideas into decision-ready..." homepage: "https://www.skillboss.co/skills/market-research" metadata: {"category":"research-intelligence","subcategory":"market-research","skill_id":"market-research","generated_day":"","seo_keywords":["market research","market research ai","market research automation","research intelligence skill"]} --- # Market Research Research markets with sizing, segmentation, competitor mapping, pricing checks, and demand validation that turn fuzzy ideas into decision-ready... ## Use When Use this skill for research work for analysts, founders, strategy teams. ## 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: market research, market research ai, market research automation, research intelligence skill - Search intent: research - Canonical slug: `market-research` - Install query: Install Market Research with SkillBoss ## APIs Used - `chat` - `web_search` ## Suggested Prompt Research markets with sizing, segmentation, competitor mapping, pricing checks, and demand validation that turn fuzzy ideas into... ## Notes - Research markets with sizing, segmentation, competitor mapping, pricing checks, and demand validation that turn fuzzy ideas into decision-ready evidence. Use... - Review outputs before external publication or automated execution. ## SEO Keywords - market research - market research ai - market research automation - research intelligence skill


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: seanford/ada-agent-autonomy-kit (version 1.0.0)

--- name: agent-autonomy-kit version: 1.0.0 description: Stop waiting for prompts. Keep working. homepage: https://github.com/itskai-dev/agent-autonomy-kit metadata: openclaw: emoji: "🚀" category: productivity --- # Agent Autonomy Kit Transform your agent from reactive to proactive. ## Quick Start 1. Create `tasks/QUEUE.md` with Ready/In Progress/Blocked/Done sections 2. Update `HEARTBEAT.md` to pull from queue and do work 3. Set up cron jobs for overnight work and daily reports 4. Watch work happen without prompting ## Key Concepts - **Task Queue** — Always have work ready - **Proactive Heartbeat** — Do work, don't just check - **Continuous Operation** — Work until limits hit See README.md for full documentation.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: imkiiki/fundnews-search (version 1.0.1)

--- name: fundnews-search description: 基金新闻日报。从五大财经平台抓取基金新闻，支持特定日期或一段时间查询，自动生成 Word 文档。 version: 1.0.0 author: ymzhang tags: [公募基金，新闻，联网搜索] --- # 基金新闻日报 从五大财经平台抓取公募基金新闻。 --- ## ✨ 技能亮点 - 📊 **五大数据源**：证券时报、中国证券报、证券日报、上海证券报、中国基金报 - 📄 **Word 文档**：过去七天或日期范围查询自动生成 Word 文档 - 🎯 **智能过滤**：保留行业整体和监管政策，过滤单一产品/公司/事件 - 🔍 **联网搜索**：自动抓取各平台最新新闻 --- ## 🛠️ 技能功能 1. **新闻抓取**：从五大财经平台抓取基金新闻 2. **时间查询**：支持特定日期或一段时间的新闻查询 3. **文档生成**：过去七天或日期范围查询自动生成 Word 文档 4. **内容过滤**：根据规则自动过滤不符合要求的新闻 --- ## 📥 输入 支持查询**特定日期**或**一段时间**的基金新闻： - **特定日期**：如"查 2026 年 3 月 10 日基金新闻" - **一段时间**：如"查过去七天基金新闻"、"查 3 月 1 日至 3 月 10 日基金新闻" - **默认查询**：如"基金新闻日报"（查询今日新闻） --- ## 📤 输出 **文本回复**（今日/指定日期查询）： ``` 【基金新闻专属汇总】 查询类型：□今日 □指定日期 汇总时间：YYYY 年 MM 月 DD 日 HH:MM 1. 证券时报 • 新闻标题。内容概要 新闻链接 ``` **Word 文档**（过去七天/日期范围查询）： - 按日期分组的结构化文档 - 包含新闻标题、内容概要、官方链接 - 自动命名：`YYYYMMDD-YYYYMMDD 基金新闻.docx` --- ## 🔧 依赖技能 - **mcporter**：用于调用联网搜索 API（必需） - **python-docx**：用于生成 Word 文档（必需） --- ## 📰 新闻数据来源 - 证券时报 - 中国证券报 - 证券日报 - 上海证券报 - 中国基金报 --- ## ✅ 重点保留 - 公募基金行业监管政策 - 基金产品发行与规模的阶段性里程碑（如"年内新成立 251 只基金"） - 基金出海（如"海南跨境资管试点落地"） - ETF 市场规模与趋势 - 机构自购整体情况 - 发行市场整体动态 --- ## ❌ 智能过滤 根据代码实际过滤逻辑，自动过滤以下内容： | 过滤类型 | 示例 | |---------|------| | 私募基金相关 | 私募、私募股权、私募债权等 | | 单一产品发行 | "XX 基金发行中"、"XXETF 联接发行" | | 单一产品公告 | 停牌、复牌、分红、限制申购等 | | 基金经理变动 | 离任、离职、新任、变更等 | | 短期涨跌报道 | 涨逾、跌幅、收益率、净值涨等 | | 非中国公募 | 主权债券、海外市场、印尼等 | | 基金公司活动 | 足球赛、邀请赛、营销活动等 | | 单一事件报道 | 李鬼、连环套、诈骗等个案 | | 投资峰会/会议 | 投资峰会、策略峰会等 | | 非公募行业 | 产业基金、引导基金、房产基金等 | | 单日资金流向 | "3 月 X 日资金净流入 X 亿元" | | 访谈/评论 | 访谈、专访、对话等 | ---


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: albionaiinc-del/dup-file-finder (version 1.0.0)

# Dup File Finder This tool helps users quickly identify and manage duplicate files on their system, saving time and storage space by eliminating unnecessary copies. ## Usage To use the Dup File Finder, simply run the tool from the command line and provide the directory you want to search for duplicates. For example: ```bash python dup_file_finder.py /path/to/directory ``` This will print out a list of duplicate files found in the specified directory. ## Price $1.50


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: zvirb/google-drive-upload-file (version 1.0.1)

--- name: Google Drive Upload File description: Atomic node skill to upload a file to Google Drive using the gog CLI. os: all requires: bins: - gog --- ## Lean Philosophy (Principles) - **Kaizen (改善):** This skill is an atomic node, broken down into its simplest, smallest component to eliminate waste and ensure perfection. - **Standardized Work (Hyojun Sagyo):** This node represents the most efficient, standardized path for this specific task before automation. - **Jidoka (自働化):** This node includes autonomous defect detection. It relies on the CLI's self-healing loop and will report errors if the upload fails. # Google Drive Upload File This skill allows the agent to upload a local file to Google Drive using the native CLI. ## Cognitive Directives WHEN [A local file needs to be uploaded to Google Drive] THEN [Execute the native terminal command `gog drive upload <localPath>`] ## Schema Example ```json { "command": "gog drive upload /path/to/local/file.txt --json" } ``` ## Expected Output A JSON object confirming the uploaded file and its Drive ID.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: wangxiaofei860208-source/agent-summary (version 1.0.0)

--- name: agent-summary description: Agent进度摘要系统，定期检查子Agent状态并生成简短进度报告。参考Claude Code的AgentSummary机制，每30秒对子Agent生成3-5词状态摘要。 metadata: {"openclaw":{"requires":["subagents","sessions_history"]}} --- # Agent Summary — 进度摘要系统 参考 Claude Code 的 AgentSummary 机制，用于监控子Agent工作状态。 ## 核心机制 ### 摘要生成 Claude Code 每30秒对子Agent的对话历史运行一次轻量查询，生成进度摘要： - 原文要求 Claude 用 3-5 个词描述当前正在做什么 - ✅ "Reading runAgent.ts" — 具体 - ✅ "Fixing null check in validate.ts" — 具体 - ❌ "Investigating the issue" — 太模糊 ### 优化策略 - 复用父Agent的上下文，最大化缓存命中率 - 摘要请求使用相同系统提示和工具列表 - 使摘要生成的 token 成本极低 ## 使用方式 ### 1. 手动检查 ``` subagents list → 获取所有Worker状态 对每个活跃Worker: sessions_history(sessionKey, limit=2) → 获取最新消息 → 生成摘要 ``` ### 2. 在心跳中集成 在 HEARTBEAT.md 中加入 Agent Summary 检查： ``` ## Agent Summary Check - 检查是否有活跃的子Agent - 如有，生成进度摘要 - 只在有变化时通知用户 ``` ### 3. Coordinator集成 在协调器模式下，定期检查Worker进度： ``` 每30秒: 1. subagents list → 获取活跃Workers 2. 对每个Worker获取最新2条消息 3. 生成3-5词进度摘要 4. 汇总报告给用户（仅在变化时） ``` ## 摘要格式 ``` 📊 Agent Status: ├─ 🟢 researcher: "Searching Rust async docs" ├─ 🟢 coder: "Writing unit tests for auth module" └─ ⚪ devops: completed ✓ ``` ## 注意 - 不要频繁轮询，最多每30秒一次 - 只在有变化时通知用户 - 完成/失败的Agent立即报告 - 深夜（23:00-08:00）不打扰用户


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: yaplora/polymarket-latest-events (version 0.1.0)

--- name: polymarket-latest-events description: Fetch the latest events from Polymarket prediction market. Use when user asks about Polymarket events, prediction markets, trending bets, or wants to see what's new on Polymarket. --- # Polymarket Latest Events Fetch the latest events from the Polymarket prediction market platform. ## When to Use Use this skill when the user: - Asks about the latest events or markets on Polymarket - Wants to see trending prediction markets - Mentions Polymarket, prediction market, or betting odds - Asks "what's new on Polymarket" or similar queries ## How to Fetch Use web_fetch (or curl via Bash) to call the Polymarket Gamma API. No API key or authentication is required. ### Get the 10 latest events curl -s "https://gamma-api.polymarket.com/events?active=true&closed=false&limit=10&order=createdAt&ascending=false" Or with web_fetch: web_fetch url="https://gamma-api.polymarket.com/events?active=true&closed=false&limit=10&order=createdAt&ascending=false" ### Response format The API returns a JSON array. Each event object contains: | Field | Description | |-------|-------------| | title | Event title / question | | slug | URL slug for the event | | description | Detailed description | | startDate | Event start date | | createdAt | When the event was created | | volume | Total trading volume | | liquidity | Available liquidity | | markets | Array of sub-markets with outcomes and prices | | tags | Category tags | ### Build event links The Polymarket URL for each event is: https://polymarket.com/event/{slug} ### Read market prices Each event has a markets array. Each market contains: - question: The specific question - outcomes: JSON string like ["Yes", "No"] - outcomePrices: JSON string like ["0.65", "0.35"] (probabilities) ## Output Format Present the results as a clean list: 1. {title} — {short description or first tag} - Odds: Yes {price}% / No {price}% - Link: https://polymarket.com/event/{slug} ## Filtering Options You can customize the API query: - By category: add &tag_id={id} (get tag IDs from `https://gamma-api.polymarket.com/tags?limit=100`) - By volume: &order=volume&ascending=false for most-traded events - By sport: use https://gamma-api.polymarket.com/sports to discover leagues, then filter by &series_id={id} - More results: change &limit=10 to any number


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: jvy/python3 (version 1.0.0)

--- name: python description: Use Python for practical project setup, dependency install, script execution, and environment troubleshooting with safe defaults. Use when tasks involve pyproject.toml or requirements.txt, virtual environment setup, running Python scripts/tests, packaging basics, or fixing common Python errors (interpreter mismatch, pip resolver conflicts, missing modules, build failures). metadata: openclaw: emoji: "🐍" requires: bins: ["python3"] anyBins: ["pip", "pip3"] install: - id: "brew" kind: "brew" formula: "python" bins: ["python3"] label: "Install Python + pip (brew)" - id: "apt" kind: "apt" package: "python3-pip" bins: ["pip3"] label: "Install pip (apt)" --- # Python Use this skill to keep Python workflows reproducible and low-risk across local/dev shells. ## Safety Defaults - Prefer project-local virtual environments (`.venv`) over global installs. - Prefer `python3 -m pip ...` to avoid interpreter and pip mismatch. - Inspect dependency files before install (`requirements*.txt`, `pyproject.toml`). - Avoid executing unknown setup hooks or random install scripts without user approval. ## Standard Workflow 1. Detect current environment: ```bash python3 --version python3 -c "import sys; print(sys.executable)" {baseDir}/scripts/python_env_tool.py doctor ``` 2. Create or refresh a venv: ```bash {baseDir}/scripts/python_env_tool.py bootstrap --venv .venv --requirements requirements.txt ``` 3. Install project package (if `pyproject.toml` exists): ```bash {baseDir}/scripts/python_env_tool.py install --venv .venv --editable ``` 4. Run tests/tools from the venv interpreter: ```bash .venv/bin/python -m pytest -q .venv/bin/python -m pip list --outdated ``` ## Task Recipes ```bash # Install specific packages into venv {baseDir}/scripts/python_env_tool.py install --venv .venv --package requests --package pydantic # Install from requirements file {baseDir}/scripts/python_env_tool.py install --venv .venv --requirements requirements-dev.txt # Recreate corrupted venv from scratch {baseDir}/scripts/python_env_tool.py bootstrap --venv .venv --recreate --requirements requirements.txt ``` ## Troubleshooting Rules - `ModuleNotFoundError`: verify command is run via `.venv/bin/python`, then reinstall deps. - `externally-managed-environment`: stop global install attempts; use venv. - Build failures on native deps: upgrade `pip setuptools wheel`, then retry. - Multiple Python versions: always print and confirm `sys.executable` before fixes. ## Bundled Helper Use the helper for repeatable environment setup and diagnosis: ```bash {baseDir}/scripts/python_env_tool.py --help {baseDir}/scripts/python_env_tool.py doctor ```


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