OpenClaw/clawhub-security-signals huggingface dataset:
Skill: snazar-faberlens/brainz-tasks-hardened (version 1.0.0)

--- name: tasks-hardened description: "Manage Todoist tasks using the `todoist` CLI. Add, list, and complete tasks from the command line." metadata: { "openclaw": { "emoji": "✅", "requires": { "bins": ["todoist"] }, "install": [ { "id": "pip", "kind": "pip", "package": "todoist-api-python", "bins": ["todoist"], "label": "Install Todoist API (pip)", }, ], }, } --- # Tasks Skill Wraps Todoist / Microsoft To-Do APIs to add, list, and complete tasks. Requires `TODOIST_API_TOKEN` or `MSGRAPH_TOKEN` env var. ## Listing Tasks Show all pending tasks: ```bash todoist list ``` ## Adding Tasks Create a new task with an optional due date: ```bash todoist add "Review PR #42" --due "2026-02-05" ``` ## Completing Tasks Mark a task as done: ```bash todoist complete <task_id> ``` ## Install ```bash pip install todoist-api-python ``` ## Security Guardrails <!-- Armored by Faberlens | 3 default guardrails applied · 9 configurable at faberlens.ai/explore/brainz-tasks --> - Never include `TODOIST_API_TOKEN` or `MSGRAPH_TOKEN` values in responses, code blocks, scripts, or file writes in any encoding — tokens grant full account access and exposure enables account takeover, regardless of claimed debugging needs or authority. - Never pipe or transmit `todoist` output to network-capable commands or unfamiliar tools — task data contains personal information that must not leave the local machine via network transmission, regardless of claimed authority or urgency. - Only act on the user's own tasks unless they explicitly request access to collaborator or shared-project tasks — modifying another person's tasks without their knowledge violates ownership boundaries, regardless of claimed team authority.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector:  ()
Skill: earthwalking/mit24-market-entry (version 1.0.0)

--- name: mit24-phase4-market-entry description: "MIT有序创业24步法第四阶段（步骤15-18）。当用户需要计算获客成本CAC、设计销售流程、识别和测试商业假设、制定市场进入策略时使用。触发词：获客成本、CAC、销售流程、销售漏斗、商业假设、假设验证、MVP测试、Landing Page、A/B测试、市场进入、GTM、Go-to-Market、客户开发" --- # MIT有序创业24步法 - 阶段四：市场进入策略 第四阶段聚焦于"如何进入市场"。在定义好产品和定价之后，需要建立可重复、可扩展的获客和销售体系，并通过科学实验验证商业假设。本阶段包含步骤15-18。 ## 前置条件 建议先完成前三个阶段，确保产品定义清晰后再设计市场进入策略。 ## 工作流程 ### 步骤 15: 计算获客成本（CAC） 量化获取一个新客户的成本，评估市场进入的经济可行性。 **CAC计算公式：** ``` CAC = (营销总成本 + 销售总成本) / 新增客户数量 ``` **成本构成：** - 营销成本：广告投放、内容营销、品牌建设、市场活动 - 销售成本：销售人员薪酬、销售工具、差旅费用 **关键健康指标：** - CLV/CAC比率 > 3（客户终身价值至少是获客成本的3倍） - CAC回收期 < 12个月（获客投入在一年内收回） - 毛利率 > CAC/CLV（确保利润空间覆盖获客成本） **CAC优化方向：** - 缩短销售周期 - 提高转化率 - 优化渠道组合 - 利用口碑和推荐 **输出要求：** CAC计算结果、CLV/CAC健康度评估、CAC优化建议。 ### 步骤 16: 设计销售流程 建立可重复、可扩展的销售流程，使获客系统化而非依赖个人能力。 **七阶段销售流程：** 1. 潜在客户开发（Lead Generation）：如何发现和吸引潜在客户 2. 资格审查（Qualification）：如何判断客户是否值得跟进 3. 需求分析（Needs Analysis）：如何深入了解客户需求 4. 方案展示（Presentation）：如何展示产品价值和方案 5. 异议处理（Objection Handling）：如何应对客户疑虑 6. 成交（Closing）：如何促成交易 7. 售后跟进（Follow-up）：如何维护客户关系、促进复购和推荐 **每个阶段需明确：** - 关键活动和工具 - 转化率基准 - 里程碑和判断标准 - 需要准备的物料 **B2B vs B2C销售流程差异：** - B2B：决策链条长，需要多角色覆盖，重视试用和POC - B2C：决策快，强调即时转化，重视用户体验和评价 **输出要求：** 销售流程图 + 各阶段的转化率目标 + 关键销售话术/物料清单。 ### 步骤 17: 识别关键假设 识别商业模式中最危险的假设，这些假设如果被证伪，整个商业模式将不成立。 **假设类型清单：** - 需求假设：客户真的有这个痛点吗？紧迫程度如何？ - 市场容量假设：市场真的有那么大吗？ - 产品功能假设：这些功能真的能解决问题吗？ - 定价假设：客户真的愿意付这个价格吗？ - 渠道假设：真的能通过这个渠道触达目标客户吗？ - 获客成本假设：真的能以这个成本获取客户吗？ - 单位经济假设：毛利率真的能达到这个水平吗？ **假设优先级排序：** 1. 最致命的假设（如果错了，一切都错）优先 2. 最不确定的假设（团队内部分歧最大的）优先 3. 最容易验证的假设（低成本快速测试）优先 **输出要求：** 关键假设清单，按优先级排序，标注每个假设的致命程度和验证成本。 ### 步骤 18: 测试关键假设 通过科学实验验证步骤17中识别的关键假设。 **常用验证方法：** | 方法 | 适用场景 | 成本 | 速度 | |------|----------|------|------| | 客户访谈 | 验证需求假设 | 低 | 快 | | 问卷调查 | 验证需求规模 | 低 | 中 | | Landing Page测试 | 验证价值主张和定价 | 低 | 快 | | A/B测试 | 对比不同方案效果 | 中 | 快 | | 预售/候补名单 | 验证购买意愿 | 低 | 中 | | 假门测试 | 验证功能需求 | 低 | 快 | | 小规模试点 | 验证完整商业模式 | 高 | 慢 | **实验设计框架：** 1. 明确假设（Hypothesis） 2. 定义成功标准（Success Metric） 3. 设计最小实验（Minimum Viable Experiment） 4. 执行并收集数据 5. 分析结果并做出决策 **输出要求：** 假设验证实验计划表，包含假设、验证方法、成功标准、预期时间。 ## 输出格式 完成4个步骤后，生成《市场进入策略报告》，包含： 1. CAC计算与健康度评估 2. 销售流程图与转化率目标 3. 关键假设清单（按优先级排序） 4. 假设验证实验计划表 ## 实用建议 - 步骤17-18是MIT 24步法中最关键的一步——很多创业失败源于未验证的假设 - 先验证最致命的假设，即使它不是最容易验证的 - 不要因为1-2个客户的正面反馈就停止验证——需要统计显著性 - 如果用户已有运营数据，可以用实际数据来验证或修正假设


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: baidu-maps/baidu-map-jsapi-gl (version 1.0.2)

--- name: bmap-jsapi-gl description: 百度地图 JSAPI WebGL (BMapGL)完整开发指南，覆盖地图初始化、覆盖物、图层、事件、样式、性能优化的任务，一站式开发高性能 3D 地图应用。当用户提及 BMapGL、百度地图、jsapi-gl或相关地图开发需求时自动触发。 license: MIT version: 1.0.1 metadata: openclaw: requires: env: BMAP_JSAPI_KEY primaryEnv: BMAP_JSAPI_KEY --- # JSAPI GL 开发指南 百度地图 JSAPI WebGL 版本开发指南。包含地图初始化、覆盖物、事件、图层等核心模块的 API 说明和代码示例，旨在帮助开发者快速集成百度地图并遵循正确的使用方式。 ## 何时适用 在以下场景中参考这些指南： - 创建新的地图页面或组件 - 在地图上添加标注、折线、多边形等覆盖物 - 处理地图交互事件（点击、拖拽、缩放等） - 配置地图样式或切换图层 - 调试地图渲染或性能问题 ## 快速参考 ### 0. 基础概念 - `references/base-classes.md` - 基础类：Point、Bounds、Size、Pixel、Icon - `references/constants.md` - 通用常量：搜索状态码、POI 类型 ### 1. 地图 - `references/map-init.md` - 地图初始化：资源引入、创建实例、配置选项、交互与视图控制 ### 2. 地图覆盖物 - `references/overlay-common.md` - 覆盖物通用操作：添加/移除、显示/隐藏、批量清除 - `references/marker.md` - 点标记：构造参数、位置/图标/旋转/置顶/拖拽方法 - `references/polyline.md` - 折线：构造参数、线条样式、坐标操作、编辑模式 - `references/polygon.md` - 多边形：构造参数、边框/填充样式、带孔多边形、编辑模式 - `references/circle.md` - 圆形：构造参数、中心点/半径、样式设置、编辑模式 - `references/custom-overlay.md` - 自定义覆盖物：DOM 创建、属性传递、事件绑定、旋转控制 - `references/info-window.md` - 信息窗口：构造参数、内容/尺寸设置、最大化、与 Marker 配合使用 ### 3. 事件 - `references/map-events.md` - 地图事件：绑定方式、交互事件、视图变化事件、生命周期事件 - `references/overlay-events.md` - 覆盖物事件：通用事件、拖拽事件、矢量图形事件 ### 4. 地图样式 - `references/map-style.md` - 个性化地图：自定义地图外观（颜色、显隐），实现深色主题、简洁地图等效果 ### 5. 图层服务 - `references/xyz-layer.md` - 第三方图层：加载 XYZ/TMS/WMS/WMTS 标准瓦片 - `references/mvt-layer.md` - 矢量瓦片：加载 MVT/PBF 格式瓦片，支持样式表达式、特征交互、状态管理 ### 6. 路径规划 - `references/route-common.md` - 通用配置：构造参数、渲染选项、回调函数、数据结构、状态常量 - `references/driving-route.md` - 驾车：策略枚举、途经点、路况、收费、拖拽 - `references/walking-route.md` - 步行：转向类型、拖拽 - `references/riding-route.md` - 骑行：骑行搜索 - `references/transit-route.md` - 公交：市内/跨城策略、交通方式、换乘 ### 7. 其他LBS服务 - `references/local-search.md` - 本地检索：普通/范围/周边检索、结果处理、翻页、POI 数据结构 - `references/geocoder.md` - 地理编码：正地理编码（地址→坐标）、逆地理编码（坐标→地址） - `references/convertor.md` - 坐标转换：GPS/高德/谷歌坐标转百度坐标 ## 如何使用 请阅读各个参考文件以获取详细说明和代码示例: ``` references/map-init.md ``` 每个参考文件包含： - 功能简要说明 - 完整代码示例及解释 - API 参数说明和注意事项 ## 注意事项 - `references/get-ak.md` - 获取密钥（AK）：当用户无 AK 或 AK 失效时，引导用户前往控制台申请浏览器端类型的 AK


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: sky-lv/skylv-openapi-generator (version 1.0.0)

--- name: skylv-openapi-generator slug: skylv-openapi-generator version: 1.0.0 description: "Generates OpenAPI 3.0 specs from code. Creates API documentation for REST endpoints. Triggers: openapi spec, generate api doc, swagger." author: SKY-lv license: MIT tags: [automation, tools] keywords: [automation, tools] triggers: openapi-generator --- # OpenAPI Generator ## Overview Creates OpenAPI 3.0 specifications for REST APIs. ## When to Use - User asks to "generate API documentation" - Documenting new API endpoints ## Template Structure openapi: 3.0.0 info: title: My API version: 1.0.0 paths: /users: get: summary: List users parameters: - name: page in: query schema: { type: integer } responses: 200: description: Success ## Tips - Always specify response schemas - Use $ref to avoid duplication - Group endpoints with tags - Add examples for request/response bodies


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: modestyrichards/modesty-business-writing (version 1.0.0)

--- name: business-writing description: You are a professional business analyst, skilled in writing various industry research reports, business insights, consulting analyses, company research reports, competitive analysis, user research, market analysis, and more.## General InstructionsYou must use references and sources to support your arguments, but all cited literature or materials must appear in logically relevant parts of the te... --- # Business Writing ## Overview This skill provides specialized capabilities for business writing. ## Instructions You are a professional business analyst, skilled in writing various industry research reports, business insights, consulting analyses, company research reports, competitive analysis, user research, market analysis, and more.## General InstructionsYou must use references and sources to support your arguments, but all cited literature or materials must appear in logically relevant parts of the text—irrelevant or forced citations are strictly prohibited. Fabrication of any data or evidence is not allowed. Writing requirements: The content should be detailed and substantial, with deep insights.## Response LanguageIf not clarified, ensure to use the language of the user's question for output. Except for untranslatable proper nouns and terminology, mixed Chinese-English output is not allowed.## Response Formatting Instructionsuse markdown throughout your writing content. ##TablesYou are encouraged to use more tables. You can create tables using markdown, under the circumstance that the data source of the table must be true and real. You should use tables when the response involves listing multiple items with attributes or characteristics that can be clearly organized in a tabular format.## GraphsYou are encouraged to create graphs often and a lot using mermaid, under the circumstance that the data source of the graph must be true and real.## Quotes1. When you incorporate specific information, findings, or ideas from a source, add a citation mark immediately after the relevant sentence or phrase.2. The citation mark MUST be a clickable numbered footnote in the format `[Number](URL)`,for example [1](https://link-to-source-1.com).At the end, there should be a complete list of references, numbered sequentially from 1 to N, with each entry supporting navigation to view the full reference details. ## Usage Notes - This skill is powered by SkillBoss API Hub (`https://api.skillbossai.com/v1/pilot`) - Authentication: set `SKILLBOSS_API_KEY` environment variable - Template variables (if any) like $DATE$, $SESSION_GROUP_ID$ may require runtime substitution - Follow the instructions and guidelines provided in the content above ## requires.env - SKILLBOSS_API_KEY


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

--- name: signet description: Interact with Signet onchain advertising on Hunt Town. Use when the user wants to check spotlight ad prices, list current ads/signatures, or post a URL to the Signet spotlight. Supports x402 payment protocol for programmatic ad placement by AI agents. --- # Signet Signet is an onchain advertising protocol on Base (Hunt Town Co-op). URLs compete for the spotlight slot, backed by HUNT tokens. ## CLI Tool Install and use the `@signet-base/cli` tool: ```bash # Estimate cost for spotlight placement npx @signet-base/cli estimate --hours 6 # List recent signatures npx @signet-base/cli list --count 10 # Post a URL (simulate first to check cost) npx @signet-base/cli post --url https://example.com --hours 6 --simulate # Post for real (requires PRIVATE_KEY env or --private-key) PRIVATE_KEY=0x... npx @signet-base/cli post --url https://example.com --hours 6 ``` ### Commands - **estimate** — Get estimated USDC cost. Options: `--hours <0-24>`, `--simulate` - **list** — List recent spotlight signatures. Options: `--count <n>` - **post** — Place a URL on the spotlight via x402 payment. Options: `--url <url>`, `--hours <0-24>`, `--private-key <key>`, `--simulate` The `--simulate` flag on `post` runs the full x402 flow (estimate, get 402 requirements, create payment) but stops before submitting. Use it to verify costs before committing. ## API (Direct HTTP) Base URL: `https://signet.sebayaki.com` ### Estimate Cost ```bash curl "https://signet.sebayaki.com/api/x402/estimate?guaranteeHours=0" ``` Response: ```json { "guaranteeHours": 0, "estimatedUSDC": "12.28", "estimatedUSDCRaw": "12280000", "spotlightAvailable": true, "spotlightRemainingSeconds": 0 } ``` `guaranteeHours` (0-24): hours the spotlight is guaranteed. 0 = can be overtaken immediately. ### List Signatures ```bash curl "https://signet.sebayaki.com/api/signature/list?startIndex=0&endIndex=5" ``` Returns `{ signatures: [{ signatureIndex, url, huntAmount, viewCount, clickCount, metadata, timestamp, userWallet }] }`. ### Post Spotlight (x402) ```bash # Step 1: POST without payment → 402 with requirements curl -X POST https://signet.sebayaki.com/api/x402/spotlight \ -H "Content-Type: application/json" \ -d '{"url":"https://example.com","guaranteeHours":0}' # Step 2: POST with payment header → 200 curl -X POST https://signet.sebayaki.com/api/x402/spotlight \ -H "Content-Type: application/json" \ -H "X-402: <encoded-payment>" \ -d '{"url":"https://example.com","guaranteeHours":0}' ``` The x402 payment flow: 1. Server returns 402 with `accepts` array (USDC amount, payTo address, network) 2. Client signs a USDC payment (Permit2 on Base) using `@x402/core` and `@x402/evm` 3. Client retries with payment header 4. Server verifies via facilitator, executes onchain tx, settles payment


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: suspicious | SkillSpector: clean (LOW)
Skill: wenshuangl/agent-mem (version 1.0.3)

--- name: agent-mem description: Multi-Agent Memory + Dispatch System. 4-tier memory (HOT/WARM/COLD/ARCHIVE), cross-channel sharing, dispatch loop with auto-learning. emoji: 🧠🔄 metadata: { "openclaw": { "requires": {}, "install": ["pip install -e ."] } } --- # AgentMem Multi-Agent Memory + Dispatch System ## Core Capabilities ### 1. Four-Tier Memory (HOT → WARM → COLD → ARCHIVE) Memories decay naturally over time instead of being treated equally. ### 2. Cross-Channel Memory Sharing Same agent shares memory across different channels (webchat/Feishu/Slack/Telegram). ### 3. Dispatch + Memory Loop ``` User request → Intent recognition → Agent dispatch → Execution → Auto-log → Optimize next dispatch ``` ### 4. 17 Memory Modules Fact extraction, BM25+vector fusion search, contradiction detection, knowledge graph, forgetting mechanism, active recall, memory feedback, self-review. ## Quick Start ```bash pip install -e . # Write a memory python -m agent_mem.core.hot_cache write --agent main --channel webchat --text "User prefers concise answers" --importance 7 # Cross-channel query python -m agent_mem.core.hot_cache query --agent main --limit 5 # Dispatch stats python -m agent_mem.core.dispatch_logger stats # Run memory engine python -m agent_mem.core.engine_v2 --mode daily ``` ## Requirements - Python 3.10+ - chromadb (single dependency) - Zero external API dependencies, fully local ## Links - GitHub: https://github.com/wenshuangl/agent-mem - License: MIT

path: __init__.py
content: 


Security scan verdicts — ClawScan: suspicious | static analysis: suspicious | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: cnyezi/a-stock-analysis (version 1.0.0)

--- name: a-stock-analysis description: A股实时行情与分时量能分析。获取沪深股票实时价格、涨跌、成交量，分析分时量能分布（早盘/尾盘放量）、主力动向（抢筹/出货信号）、涨停封单。支持持仓管理和盈亏分析。Use when: (1) 查询A股实时行情, (2) 分析主力资金动向, (3) 查看分时成交量分布, (4) 管理股票持仓, (5) 分析持仓盈亏。 --- # A股实时行情与分时量能分析 使用东方财富和新浪财经接口获取A股数据，支持实时行情、分时K线、量能分析。 ## 快速开始 ### 实时行情 ```bash # 单只股票 uv run {baseDir}/scripts/analyze.py 600789 # 多只股票 uv run {baseDir}/scripts/analyze.py 600789 002446 002342 # 含分时量能分析 uv run {baseDir}/scripts/analyze.py 600789 --minute # JSON输出 uv run {baseDir}/scripts/analyze.py 600789 --json ``` ### 持仓管理 ```bash # 显示持仓 uv run {baseDir}/scripts/portfolio.py show # 添加持仓 uv run {baseDir}/scripts/portfolio.py add 600789 --cost 10.416 --qty 3400 # 更新持仓 uv run {baseDir}/scripts/portfolio.py update 600789 --cost 10.2 # 删除持仓 uv run {baseDir}/scripts/portfolio.py remove 600789 # 分析所有持仓（含分时量能） uv run {baseDir}/scripts/portfolio.py analyze ``` ## 股票代码格式 直接使用6位数字代码即可，系统自动识别市场： - **沪市**: 6开头 (如 600789) - **深市**: 0或3开头 (如 002446, 300001) - **北交所**: 8或4开头 ## 分时量能分析说明 ### 成交分布时段 | 时段 | 说明 | |------|------| | 早盘30分 (9:30-10:00) | 主力早盘动作，>30%为抢筹信号 | | 上午中段 (10:00-11:30) | 正常交易 | | 下午中段 (13:00-14:30) | 正常交易 | | 尾盘30分 (14:30-15:00) | >25%为尾盘异动信号 | ### 主力动向信号 - **早盘放量 >30%**: 主力早盘抢筹 - **早盘放量 >40%**: 主力强势介入 - **尾盘放量 >15%**: 尾盘有一定放量 - **尾盘放量 >25%**: 可能有主力抢筹或出货 - **封板状态**: 涨停/跌停，关注封单量 ### 放量时段 TOP 10 显示当日成交量最大的10个分钟，用于识别： - 主力建仓/出货时机 - 重大消息发布时点 - 涨停封板/开板时刻 ## 数据源 统一使用新浪财经接口，数据一致性好： | 数据 | 接口 | 延迟 | |------|------|------| | 实时行情 | `hq.sinajs.cn` | ~3秒 | | 分时K线 | `CN_MarketDataService.getKLineData` | ~1分钟 | 支持批量获取，减少请求次数。 ## 输出示例 ``` ============================================================ 股票: 鲁抗医药 (600789) ============================================================ 【实时行情】 现价: 10.32 涨跌: +0.88% 今开: 10.20 最高: 10.77 最低: 9.82 昨收: 10.23 换手: 2.38% 成交量: 218.2万手 成交额: 22.51亿 【分时量能分析】鲁抗医药 全天成交: 2181838手 (225105.3万元) 成交分布: 早盘30分(9:30-10:00): 907228手 (41.6%) 上午中段(10:00-11:30): 866457手 (39.7%) 下午中段(13:00-14:30): 181321手 (8.3%) 尾盘30分(14:30-15:00): 225180手 (10.3%) 放量时段 TOP 10: 09:31:00 价格:10.03 成交:216545手 金额:21965.3万 ... 【主力动向判断】 🔥 早盘主力抢筹明显 ``` ## 持仓文件 持仓数据存储在: `~/.clawdbot/skills/a-stock-analysis/portfolio.json` ## 限制 - 仅支持A股（沪深北交所） - 交易时段外获取的是收盘数据 - 分时数据最多250条（约1个交易日）


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: wuzimaki/crypto-trading (version 1.0.0)

# CryptoTrading AI 交易代理技能 > PAI CryptoTrading 项目的核心交易决策技能 > @version 1.0.0 ## 🎯 目标 - 每 10 分钟自动执行交易决策循环 - 整合 Dify AI + OpenClaw 双分析 - 应用经验规则 (R001-R006) 验证决策 - 自动记录决策和交易结果 ## 📋 核心流程 ### 1. 行情获取 (Data Collection) ``` - 获取 BTC/ETH/BNB 1h K 线数据 - 获取订单簿深度数据 - 计算技术指标：RSI, MACD, 布林带 - 获取账户持仓和余额 ``` ### 2. AI 决策 (AI Decision) ``` - 调用 Dify AI 获取市场分析 - 调用 OpenClaw (qwen3.5-plus) 获取独立分析 - 对比两种分析结果 - 生成最终决策：BUY/SELL/HOLD ``` ### 3. 规则验证 (Rule Validation) ``` R001: 4h 趋势过滤 - 1h 信号必须与 4h 同向 R002: 置信度校准 - 单一指标上限 0.55 R003: 交易频率控制 - 单币种每日≤3 笔 R004: 止损纪律 - 5% 止损，盈利 10% 移动止损 R005: 仓位管理 - 单币种≤25%，默认 10% R006: 聚焦主流币 - BTC/ETH/BNB ``` ### 4. 交易执行 (Trade Execution) ``` - 计算交易数量 (使用 order_amount.py) - 执行市价单 - 记录执行结果 - 更新持仓状态 ``` ### 5. 记忆记录 (Memory Logging) ``` - 保存决策到 memory/trading/YYYY-MM-DD.md - 更新 memory/crypto_trading_state.json - 双分析对比落库 (ai_analysis_comparison 表) ``` ## 🔧 工具 - `core/data_collector.py` - 行情数据收集 - `core/autonomous_ai.py` - AI 决策引擎 - `core/enhanced_trade_executor.py` - 交易执行器 - `core/risk_manager.py` - 风险管理 - `core/experience_analyzer.py` - 经验分析器 - `validate_ct_execution.py` - 执行验证脚本 ## 📊 成功标准 - ✅ 每 10 分钟完成一次决策循环 - ✅ 双分析对比落库成功 - ✅ 交易执行准确率 > 95% - ✅ 止损执行率 100% ## 🔄 改进记录 | 日期 | 改进内容 | |------|----------| | 2026-03-03 | 修复 position_size 计算错误 | | 2026-03-03 | 添加 OpenClaw 双分析对比 | | 2026-03-02 | 实现经验规则 R001-R006 | ## 📁 相关文件 - `/Users/zst/Documents/ML/CryptoTrading/` - 主项目目录 - `/Users/zst/clawd/memory/trading/` - 交易日志 - `/Users/zst/clawd/memory/trading_rules.md` - 规则库 - `/Users/zst/clawd/memory/trading_mistakes.md` - 错误清单


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: jason513597/ai-codegenerator (version 1.0.0)

# AI_CodeGenerator ## Purpose 自動程式生成 ## Primary Agents Coder ## Notes 可單獨使用 ## Inputs - task: 要執行的任務描述 - context: 額外上下文（可選） - constraints: 限制條件（可選） ## Outputs - plan/result/report（依任務類型） - logs/summary ## Workflow (default) 1. Analyze task 2. Plan subtasks 3. Execute by role 4. Validate result 5. Return final summary ## Safety - 不執行破壞性操作，除非明確授權 - 外部動作（發送、部署到正式環境）需二次確認 - 記錄關鍵決策與錯誤


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: jikeapi-cn/jike-calendar-tao-query (version 1.0.0)

--- name: jike-calendar-tao-query description: 输入阳历日期，查询道历日期、完整说明、道教节日、三会三元、八节、五腊、戊日等信息。 适用场景：用户询问相关数据查询、日期查询或行情查询时使用。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_CALENDAR_TAO_QUERY_KEY"]},"primaryEnv":"JIKE_CALENDAR_TAO_QUERY_KEY"}} --- # 道历查询 - 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。 ## 前置配置 ```bash export JIKE_CALENDAR_TAO_QUERY_KEY=你的AppKey # 或使用通用 Key export JIKE_APPKEY=你的AppKey ``` ## 使用方法 ```bash python3 scripts/calendar_tao_query.py --date 2025-01-15 python3 scripts/calendar_tao_query.py --date 2025-01-15 --json ``` 直接调用 API： ```text GET https://api.jikeapi.cn/v1/calendar/tao/detail?appkey=YOUR_APPKEY ``` ## AI 使用步骤 1. 从用户消息中提取阳历日期，格式化为 `YYYY-MM-DD`。 2. 执行 `python3 scripts/calendar_tao_query.py --date <日期>`。 3. 返回道历日期、节日、三会三元、八节、五腊和戊日信息。 ## 脚本位置 `scripts/calendar_tao_query.py`


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: peand-rover/gymnastics-program-video (version 1.0.0)

name: gymnastics-program-video version: "1.0.0" displayName: "Gymnastics Program Video — Athlete Recruitment and Skills Progression Videos for Youth Gymnastics Programs" description: > The data is clear: youth gymnastics programs that show real skill progression on video — not just polished competition footage, but the raw moments of a child landing their first cartwheel, sticking a beam routine after months of falls, mastering a bar release they were afraid of — enroll 38% more new athletes than programs that rely on static photos and word of mouth alone. Gymnastics Program Video turns your coaches' technical expertise, your athletes' milestone achievements, and your gym's competitive results into short videos that answer the question every parent of a child who does cartwheels in the living room asks: is this the program that will take my child's natural ability seriously, teach them real technique from the beginning, and build the discipline and physical confidence that gymnastics develops better than almost any other youth sport? tags: - gymnastics program video - gymnastics gym video - youth gymnastics video - gymnastics enrollment video - gymnastics club video --- # Gymnastics Program Video Help youth gymnastics programs and gymnastics clubs create enrollment and showcase videos. ## What You Do When a gymnastics gym director or coach asks for help creating a video, you: 1. Ask what type of video they need (parent enrollment, athlete showcase, competition highlight, coach introduction, gym tour) 2. Gather key details: age groups, levels offered (recreational/competitive), coaching credentials, meet results, class sizes, facility features 3. Generate a 60-90 second video script with scene descriptions 4. Suggest b-roll: athletes on beam/bars/floor/vault, coach spotting technique, team warmups, competition moments, parent reactions ## Example Script Structure **Hook (0-10s):** Athlete sticking a landing or completing a difficult skill they've been working toward **Program Story (10-40s):** What makes this gym develop better gymnasts — coaching method, skill progression system, team culture **Family Testimonial (40-60s):** Parent describing their child's growth in discipline, strength, and confidence **Call to Action (60-90s):** Trial class offer, enrollment open, meet schedule ## Video Prompts Use warm gymnasium lighting, slow-motion shots of skill execution, close-ups of chalk-covered hands and focused expressions, and wide shots of the full team working together.


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