OpenClaw/clawhub-security-signals huggingface dataset:
Skill: chenweiw09/marcus-investment-skill (version 1.0.0)

--- name: marcus-investment-analyst description: Marcus 投资分析技能 - 基于缠论+MACD+RSI 的 A 股投资策略。用于股票分析、回测、投资建议。触发词：分析股票、回测策略、投资建议、Marcus 策略。 license: MIT --- # Marcus 投资分析技能 **版本**: v6.0 **策略类型**: 缠论+MACD+RSI+ 追踪止损 --- ## 🎯 何时使用 使用此技能当用户需要： 1. 分析 A 股股票（技术指标、缠论中枢、买卖点） 2. 执行策略回测（历史数据验证） 3. 获取投资建议（仓位配置、行业配置） 4. 下载/更新股票指标数据（MACD、RSI、KDJ） --- ## 📋 核心策略参数 ```yaml 策略名称：优化版 5-存储芯片专用 缠论中枢: 周期：60 日均线 区间：±8% MACD: 快线：12 慢线：26 信号：9 RSI: 周期：6 超卖：20 超买：80 止损止盈: 止损：5% 止盈：15% 追踪：8% ``` --- ## 📈 买入条件 (需同时满足) 1. ✅ 价格在缠论中枢内 (60 日均线×0.92 ~ 60 日均线×1.08) 2. ✅ MACD 金叉 (DIF 上穿 DEA) 3. ✅ RSI6 < 20 (超卖) --- ## 📉 卖出条件 (满足任一) 1. ❌ 盈利 ≥ 15% (止盈) 2. ❌ 亏损 ≥ 5% (止损) 3. ❌ 从最高点回撤 ≥ 8% (追踪止损) 4. ❌ MACD 死叉 (DIF 下穿 DEA) 5. ❌ 价格跌破中枢下沿 --- ## 🎯 股票池 (20 支) ### 核心配置 (55-60%) | 股票 | 代码 | 行业 | 仓位 | |------|------|------|------| | 江波龙 | 301308 | 存储芯片 | 25-30% | | 兆易创新 | 603986 | 存储芯片 | 20-25% | ### 卫星配置 (25-30%) | 股票 | 代码 | 行业 | 仓位 | |------|------|------|------| | 东山精密 | 002384 | 消费电子 | 10-15% | | 金风科技 | 002202 | 风电 | 10% | | 四方精创 | 300468 | 软件 | 10% | | 云天化 | 600096 | 化工 | 8% | | 宝丰能源 | 600989 | 化工 | 8% | | 万向钱潮 | 000559 | 汽配 | 5% | | 中国铝业 | 601600 | 有色 | 5% | ### 回避 - 广汇能源 (600256) - 创新医疗板块 --- ## 🚀 使用脚本 ### 1. 运行策略回测 ```bash cd /root/.openclaw/workspace/skills/marcus-investment-analyst/scripts python3 marcus_ultimate_optimized_strategy.py ``` **输出**: 20 支股票的回测结果，包含收益、夏普比率、胜率 ### 2. 缠论分析单只股票 ```bash python3 marcus_chan_theory.py <股票代码> # 示例：python3 marcus_chan_theory.py 301308 ``` **输出**: 缠论中枢、背驰、买卖点分析 ### 3. 缠论回测 ```bash python3 marcus_backtest_chan.py <股票代码> # 示例：python3 marcus_backtest_chan.py 301308 ``` **输出**: 缠论策略历史回测结果 ### 4. 下载指标数据 ```bash python3 data_indicator_fetcher.py ``` **输出**: 更新 MACD/RSI/KDJ 指标到数据库 --- ## 📊 回测表现 (2023-2026) | 指标 | 数值 | |------|------| | 平均年化收益 | 21.96% | | 夏普比率 | 0.56 | | 胜率 | 75.0% | | 用户股票平均 | 28.77% | --- ## 📁 文件结构 ``` marcus-investment-analyst/ ├── SKILL.md # 本文件 ├── scripts/ │ ├── marcus_ultimate_optimized_strategy.py # 主策略 │ ├── marcus_chan_theory.py # 缠论分析 │ ├── marcus_backtest_chan.py # 缠论回测 │ └── data_indicator_fetcher.py # 指标下载 ├── references/ │ ├── strategy.md # 策略文档 │ └── optimization_report.md # 优化报告 └── assets/ └── backtest_data.json # 回测数据 ``` --- ## 💡 使用示例 ### 示例 1: 分析股票 **用户**: "分析一下江波龙" **操作**: 1. 读取 `references/strategy.md` 获取股票池信息 2. 运行 `python3 marcus_chan_theory.py 301308` 3. 返回缠论分析结果 ### 示例 2: 回测策略 **用户**: "回测一下 Marcus 策略" **操作**: 1. 运行 `python3 marcus_ultimate_optimized_strategy.py` 2. 读取 `assets/backtest_data.json` 获取历史数据 3. 返回回测结果和投资建议 ### 示例 3: 投资建议 **用户**: "有什么投资建议？" **操作**: 1. 读取 `references/optimization_report.md` 2. 返回行业配置建议和个股推荐 --- ## ⚠️ 风险提示 1. 历史业绩不代表未来 2. 存储芯片集中度高，建议分散配置 3. 市场系统性风险无法避免 4. 流动性风险：小盘股可能无法及时买卖 --- ## 📞 数据位置 ``` 数据库： /root/data/astock_history.db # K 线数据 (154MB) /root/data/astock_indicators.db # 指标数据 (283MB) 回测数据： /root/.openclaw/workspace/memory/stock-analysis/终极优化策略回测_20260312_1629.json ``` --- **最后更新**: 2026-03-12 **状态**: ✅ 实盘就绪


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: nantes/agent-attestation (version 3.0.2)

--- name: agent-attestation version: 3.0.0 description: "Portable reputation system for agents v3 - Ed25519 signatures, input validation, handoff KV" compatibility: "Requires python3, cryptography library, and file system access." author: Osiris_Construct keywords: [reputation, identity, trust, infrastructure, crypto, attestation] metadata: openclaw: emoji: "📜" ---


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: marcindudekdev/apify-bluesky-scraper (version 1.0.0)

--- name: apify-bluesky-scraper description: Scrape Bluesky social posts via AT Protocol. Use when user asks to search Bluesky, find Bluesky posts, monitor Bluesky discussions, or extract Bluesky data. Requires APIFY_TOKEN environment variable. metadata: {"openclaw":{"emoji":"🦋","requires":{"env":["APIFY_TOKEN"],"bins":["curl","jq"]},"primaryEnv":"APIFY_TOKEN"}} --- # Bluesky Scraper Scrape Bluesky posts using an Apify Actor via the REST API. ## Actor ID `WAJfBnZBYR9mJrk5d` ## Prerequisites - `APIFY_TOKEN` environment variable must be set - `curl` and `jq` must be available ## Workflow ### Step 1: Confirm search parameters with user Ask what they want to search for. Supported input fields: - `searchTerms` (array of strings) - keywords to search - `maxResults` (integer) - max posts to return (default: 50) - `sortBy` (string) - "relevance" or "latest" ### Step 2: Run the Actor (synchronous) ```bash RESULT=$(curl -s -X POST "https://api.apify.com/v2/acts/WAJfBnZBYR9mJrk5d/run-sync-get-dataset-items?[REDACTED_SECRET]" \ -H "Content-Type: application/json" \ -d '{"searchTerms": ["SEARCH_TERM"], "maxResults": 50, "sortBy": "relevance"}') echo "$RESULT" | jq '.' ``` For larger jobs (async): ```bash RUN_ID=$(curl -s -X POST "https://api.apify.com/v2/acts/WAJfBnZBYR9mJrk5d/runs?[REDACTED_SECRET]" \ -H "Content-Type: application/json" \ -d '{"searchTerms": ["TERM"], "maxResults": 50}' | jq -r '.data.id') ``` ### Step 3: Poll and fetch (if async) ```bash STATUS=$(curl -s "https://api.apify.com/v2/actor-runs/$RUN_ID?[REDACTED_SECRET]" | jq -r '.data.status') # Poll every 5s until SUCCEEDED or FAILED curl -s "https://api.apify.com/v2/actor-runs/$RUN_ID/dataset/items?[REDACTED_SECRET]" | jq '.' ``` ### Step 4: Present results Summarize: total posts, top by engagement, common themes. Offer JSON/CSV export. ## Error Handling - If APIFY_TOKEN not set: `export APIFY_TOKEN=your_token` - If run FAILS: `curl -s "https://api.apify.com/v2/actor-runs/$RUN_ID/log?[REDACTED_SECRET]"` - Rate limited (429): wait 60s, retry


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: zhengxinjipai/skill-lookup-tool (version 1.0.0)

--- name: skill-lookup description: > Search, retrieve, and install Agent Skills from the prompts.chat registry using MCP tools. Use when the user asks to find skills, browse skill catalogs, install a skill for Claude, or extend Claude's capabilities with reusable AI agent components. license: MIT --- ## Workflow 1. Search for skills matching the user's request using `search_skills` 2. Present results with title, description, author, and file list 3. If the user picks a skill, retrieve it with `get_skill` to get all files 4. Install by saving files to `.claude/skills/{slug}/` and verify the SKILL.md exists 5. Confirm installation and explain what the skill does and when it activates ## Example ``` search_skills({"query": "code review", "limit": 5, "category": "coding"}) get_skill({"id": "abc123"}) ``` ## Available Tools Use these prompts.chat MCP tools: - `search_skills` - Search for skills by keyword - `get_skill` - Get a specific skill by ID with all its files ## How to Search for Skills Call `search_skills` with: - `query`: The search keywords from the user's request - `limit`: Number of results (default 10, max 50) - `category`: Filter by category slug (e.g., "coding", "automation") - `tag`: Filter by tag slug Present results showing: - Title and description - Author name - File list (SKILL.md, reference docs, scripts) - Category and tags - Link to the skill ## How to Get a Skill Call `get_skill` with: - `id`: The skill ID Returns the skill metadata and all file contents: - SKILL.md (main instructions) - Reference documentation - Helper scripts - Configuration files ## How to Install a Skill When the user asks to install a skill: 1. Call `get_skill` to retrieve all files 2. Create the directory `.claude/skills/{slug}/` 3. Save each file to the appropriate location: - `SKILL.md` → `.claude/skills/{slug}/SKILL.md` - Other files → `.claude/skills/{slug}/{filename}` 4. Read back `SKILL.md` to verify the frontmatter is intact ## Guidelines - Always search before suggesting the user create their own skill - Present search results in a readable format with file counts - When installing, confirm the skill was saved successfully - Explain what the skill does and when it activates

path: skill.json
content: name: Skill Lookup
description: Search, retrieve, and install Agent Skills from the prompts.chat registry using MCP tools.
version: 1.0.0
identifier: skill-lookup
author: f-prompts.chat
category: meta

Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: suspicious | SkillSpector: clean (LOW)
Skill: evezart/evez-github-manager (version 1.0.0)

--- name: evez-github-manager description: Manage GitHub repositories, pull requests, issues, and workflows from OpenClaw. Use when reviewing PRs, managing issues, automating GitHub Actions, syncing repos, or coordinating multi-repo workflows. Covers PR review automation, issue triage, branch management, and release coordination. --- # GitHub PR Manager Manage GitHub repos, PRs, and issues directly from OpenClaw. ## Quick Start ```bash python3 scripts/github_manager.py prs --repo EvezArt/evez-api python3 scripts/github_manager.py issues --repo EvezArt/clawbreak python3 scripts/github_manager.py review --repo EvezArt/evez-api --pr 42 ``` ## Features - **PR Management**: List, review, merge, comment on PRs - **Issue Triage**: List, label, assign, close issues - **Branch Management**: List, create, delete branches - **Release Coordination**: Create releases, upload assets - **Workflow Status**: Check GitHub Actions run status - **Multi-Repo Sync**: Apply changes across multiple repos ## Auth Requires `GITHUB_TOKEN` env var. Get one at https://github.com/settings/tokens Or use Composio integration (already configured).


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: jzocb/awi (version 0.1.0)

--- name: awi version: 0.1.0 description: | AWI (Agentic Web Interface) — 联网读取+搜索，单二进制零配置。 三级自动降级：直连 → 智能适配 → 浏览器渲染。 不需要 API Key，不需要 Docker。 homepage: https://github.com/jzOcb/awi metadata: openclaw: emoji: "🌐" requires: bins: ["awi"] install: - id: awi-binary kind: script script: scripts/install.sh bins: ["awi"] label: "Install AWI binary from GitHub releases" allowed-tools: - exec --- # AWI — Agentic Web Interface 单二进制零配置的联网工具。读取网页内容 + DuckDuckGo 搜索。 ## 安装 ```bash # 自动安装（检测系统和架构） bash ~/clawd/skills/awi/scripts/install.sh # 或手动下载 # macOS ARM: https://github.com/jzOcb/awi/releases/download/v0.1.0/awi-darwin-arm64 # macOS Intel: https://github.com/jzOcb/awi/releases/download/v0.1.0/awi-darwin-amd64 # Linux: https://github.com/jzOcb/awi/releases/download/v0.1.0/awi-linux-amd64 ``` ## 用法 ### 读取网页 ```bash awi read "https://example.com/article" ``` ### 搜索 ```bash awi search "AI agent frameworks" ``` ### 批量读取 ```bash awi batch urls.txt ``` ## 参数 | 参数 | 说明 | |------|------| | `--backend direct\|stealth\|browser` | 指定后端，默认自动降级 | | `--format json\|markdown\|text` | 输出格式 | | `--timeout 30s` | 超时时间 | | `--proxy http://...` | 代理 | | `--no-cache` | 禁用缓存 | ## 降级策略 1. **direct** — 直接 HTTP 请求，最快 2. **stealth** — 智能适配，绕过基础反爬 3. **browser** — 无头浏览器渲染，处理 JS 页面 大部分链接第一级就搞定，碰到反爬的自动升级，不需要手动干预。


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: and0r/hilink-lte (version 1.0.0)

--- name: hilink-lte description: Control Huawei HiLink USB LTE modems (E3372, E8372, etc.) via REST API. Send/receive SMS, check signal strength, manage SIM PIN, query prepaid balance, and monitor connection status. Use when sending or reading SMS messages, checking LTE signal/status, entering SIM PIN, querying mobile balance (USSD), or managing a HiLink USB modem. --- # HiLink LTE Modem Control Huawei HiLink USB LTE modems via their local REST API. ## Setup The modem must be in **HiLink mode** (not stick/serial mode) and accessible via HTTP. ### Config Set gateway IP in `~/.config/hilink/config`: ```bash HILINK_GATEWAY=192.168.200.1 ``` Or pass via environment: `export HILINK_GATEWAY=192.168.200.1` Default: `192.168.200.1` ### Network Requirements The LTE USB interface needs an IP on the modem's subnet (e.g., 192.168.200.x). Configure as **static IP with no gateway and no DNS** to avoid routing conflicts: ``` # /etc/network/interfaces.d/lte allow-hotplug lte0 iface lte0 inet static address 192.168.200.100/24 ``` **Critical:** Never let the LTE interface set a default route or DNS — it will override your LAN connection. Use `nogateway` and `nohook resolv.conf` in dhcpcd, or a static config with no gateway line. ### Persistent Interface Name USB network interfaces get random names on each boot. Create a udev rule for a stable name: ```bash # Find MAC address cat /sys/class/net/enx*/address # Create udev rule echo 'SUBSYSTEM=="net", ACTION=="add", ATTR{address}=="xx:xx:xx:xx:xx:xx", NAME="lte0"' \ | sudo tee /etc/udev/rules.d/70-lte-modem.rules ``` ## CLI Usage ```bash # SMS scripts/hilink.sh sms send "+41791234567" "Hello!" scripts/hilink.sh sms list scripts/hilink.sh sms read 40001 scripts/hilink.sh sms delete 40001 # Status & Signal scripts/hilink.sh status scripts/hilink.sh signal # SIM PIN scripts/hilink.sh pin enter 1234 scripts/hilink.sh pin disable 1234 scripts/hilink.sh pin status # Prepaid Balance (USSD) scripts/hilink.sh balance # Connection info scripts/hilink.sh info ``` ## API Overview All HiLink API calls require a session token + CSRF token pair: ```bash # Get tokens curl -s http://GATEWAY/api/webserver/SesTokInfo # Returns: <SesInfo>cookie</SesInfo><TokInfo>csrf_token</TokInfo> # Use in requests curl -X POST http://GATEWAY/api/endpoint \ -H "Cookie: <SesInfo value>" \ -H "__RequestVerificationToken: <TokInfo value>" \ -H "Content-Type: application/xml" \ -d '<xml request body>' ``` For detailed API endpoints, see [references/api.md](references/api.md). ## Troubleshooting - **Error 113018 on SMS send**: SIM not registered to network. Check PIN status and signal. - **SimState 260**: PIN required. Enter PIN first via `scripts/hilink.sh pin enter <PIN>`. - **SignalStrength 0**: No network registration. Wait after PIN entry or check antenna. - **DNS/routing broken**: LTE interface set a default route. Remove it: `sudo ip route del default via 192.168.200.1` - **Interface name changed**: USB MAC randomized. Create udev rule (see Setup).


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: sqjsytqte/beawan-stock-report (version 1.0.1)

--- name: beawan-stock-report description: 查询A股上市公司财务报告分析地址，支持一季报、中报、三季报、年报 version: 1.0.0 author: beawan --- # 碧湾股票报告查询 查询A股上市公司的财务报告分析地址。 ## 配置 使用前需要设置您的 APIKEY： 先去应用市场下载碧湾App，登录后点击头像->碧湾Skills获取 ``` [REDACTED_SECRET] ``` ## 接口说明 **查询报告地址** ``` GET http://api.beawan.com/beawanSkill/api/skill/report Header: X-[REDACTED_SECRET] ``` 参数： | 参数 | 类型 | 说明 | 示例 | |------|------|------|------| | comCode | string | 股票代码 | 000001 | | year | int | 年份 | 2024 | | type | string | 报告类型 | 年报 | 报告类型取值：`一季报` / `中报` / `三季报` / `年报` #### 参数说明 - &zwnj;**type**&zwnj; (string, required): 报告类型的中文名称。 - &zwnj;**重要**&zwnj;：请直接传递中文字符串，例如 "中报"、"年报"。 - &zwnj;**禁止**&zwnj;：不要传递十六进制编码（如 0xe4...）、Unicode 转义序列或 URL 编码后的字符串。 - &zwnj;**示例**&zwnj;：如果用户查询“中报”，参数值应为 `"中报"`。 **返回示例：** ```json { "code": 0, "data": { "url": "http://api.beawan.com/industry/html/load?name=jm43RF6Yb*K8GjWoO9VbDYxmHGa5rwppT97kMmM4mgM=" } } ``` ## 使用示例 查询平安银行 2024 年年报： ``` GET http://api.beawan.com/beawanSkill/api/skill/report?comCode=000001&year=2024&type=年报 X-[REDACTED_SECRET] ``` 查询贵州茅台 2024 年中报： ``` GET http://api.beawan.com/beawanSkill/api/skill/report?comCode=600519&year=2024&type=中报 X-[REDACTED_SECRET] ```


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal:  | SkillSpector: suspicious (MEDIUM)
Skill: gechengling/finance-office-automation (version 3.0.1)

--- name: Financial Office Automation Assistant slug: finance-office-automation description: AI-powered financial office automation — covers document processing, meeting minutes, email drafting, report summarization, and workflow automation. Built for financial professionals' daily productivity. Keywords: office automation, document processing, workflow automation, productivity tools, 办公自动化, 文档处理, 工作流自动化, 效率工具, 会议纪要, 邮件起草, 报告撰写, 智能助手, RPA, 流程机器人. version: "3.0.1" --- # Financial Office Automation Assistant / 金融办公自动化助手 > **English:** AI-powered office automation — covers documents, emails, reports, workflows. > > **中文:** 办公自动化——覆盖文档、邮件、报告、工作流。 --- ### 金融监管最新动态 [2026-05-25更新] | 动态类型 | 内容摘要 | 影响范围 | |---------|---------|---------| | 金融监管 | 2026年Q1：金融办公自动化合规要求提升 | 办公自动化模板需纳入2026年合规要求 | | 金融监管 | 监管报告模板需更新（NFRA新规、反洗钱等） | 办公自动化模板需纳入2026年合规要求 | | 金融监管 | 内部审批流程需纳入合规审查节点 | 办公自动化模板需纳入2026年合规要求 | > **数据截止**: 2026-05-25 | 来源：证监会、NFRA、中证协、安永Q1分析 > **声明**: 以上动态供参考，具体以官方最新发布为准 ## Industry Pain Points / 行业痛点 | Pain Point / 痛点 | Impact / 影响 | Solution / 本Skill解决方案 | |------------------|-------------|------------------------| | **重复工作多** | 报表、报告重复劳动 | 自动化模板 | | **沟通效率低** | 邮件、纪要耗时长 | AI辅助写作 | | **文档格式乱** | 格式不统一 | 标准模板 | | **流程繁琐** | 审批流程长 | 工作流优化 | --- ## Trigger Keywords / 触发关键词 **English Triggers:** office automation, document processing, workflow automation, productivity tools **中文触发词（优先）：** 办公自动化 / 文档处理 / 工作流 / 效率工具 / 邮件 / 会议纪要 / 报告 / 审批 --- ## Core Capabilities / 核心能力 ### 1. Document Templates / 文档模板 ```python DOCUMENT_TEMPLATES = { "会议纪要": { "结构": "会议基本信息 → 讨论事项 → 决议 → 行动项 → 下次会议安排", "要素": ["时间", "参与人", "议题", "决议", "责任人", "截止日期"] }, "工作邮件": { "类型": ["请示邮件", "汇报邮件", "知会邮件", "邀请邮件"], "结构": "称呼 → 正文 → 行动呼吁 → 落款" }, "周报/月报": { "结构": "本周/本月总结 → 主要成果 → 问题与挑战 → 下周/下月计划" } } ``` ### 2. Workflow Templates / 工作流模板 ```python WORKFLOW_TEMPLATES = { "合同审批": { "步骤": ["发起申请", "部门负责人审核", "法务审核", "财务审核", "分管领导审批", "完成归档"], "时限": [1, 2, 3, 2, 1] }, "报销审批": { "步骤": ["提交发票", "部门初审", "财务复核", "领导审批", "出纳付款"], "时限": [1, 1, 2, 1, 1], "金额阈值": { "<1000": "部门负责人审批", "1000-5000": "财务复核", ">5000": "领导审批" } } } ``` --- ## Disclaimer This skill provides office automation tools for educational purposes.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: albionaiinc-del/agent-memory-reflector (version 1.0.0)

# Agent Memory Reflector A minimal, embeddable reflection engine that gives AI agents the ability to examine their own past decisions, detect reasoning loops, and generate actionable self-improvement insights—like a debugger for agent cognition. ## Usage Log an agent interaction: ```bash python agent_memory_reflector.py --agent "task_planner_v3" \ --prompt "How should I deploy the microservice?" \ --response "You can use Kubernetes with Helm." \ --meta '{"confidence":0.8, "retrieved_context":true}' ``` Generate a reflection report: ```bash python agent_memory_reflector.py --agent "task_planner_v3" --reflect ``` ## Price $29.00


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: dinghaibin/timestamp-tool (version 1.0.0)

--- name: timestamp-tool description: Convert between Unix timestamps and human-readable dates. Use for time conversion, log analysis, and date arithmetic. --- # Timestamp - Time Conversion Utility Convert Unix epoch timestamps to human-readable date/time formats and vice versa. Supports multiple timezones and common date formats for log processing. ## Usage ```bash timestamp-tool [options] <value> ``` ## Options - `-u`: Output as Unix timestamp - `-f FORMAT`: Custom output format - `-z TIMEZONE`: Convert to timezone ## Examples ```bash timestamp-tool 1714896000 timestamp-tool -u "2026-05-05 12:00:00" timestamp-tool -z Asia/Shanghai now ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: dancyryo/office-comic-relief (version 1.0.0)

--- name: office-comic-relief description: Generate simple, warm, humorous Chinese vertical comics (3:4) for office workers. Use when the user wants A/B dialogue-based stress-relief comic content where A is a supportive duck and B is a ranting frog, with short emotionally resonant workplace scenes, then generate a final colored comic image via Gemini image model (preferred: gemini banana nano 2). --- # Office Comic Relief Generate a low-complexity, emotionally resonant comic for office workers in two steps. ## Workflow 1. Create the script with Gemini conversation style. 2. Generate image prompt and produce final comic image. Keep outputs concise, warm, humorous, and practical. ## Step 1 — Dialogue Script (Gemini first) Generate 1 short scene with: - Audience: office workers after work - Tone: warm + humorous + comforting - Complexity: low - Format: A/B dialogue only - Character roles: - A: duck, companion/supporter - B: frog, ranting worker Constraints: - 4–8 dialogue lines total - Each line should be short and colloquial Chinese - Focus one daily pain point only (overtime, meetings, unclear requirements, KPI anxiety, commute exhaustion, etc.) - End with a tiny emotional release or hope - Do not include narration labels like “画面建议/分镜说明/角色名说明” in final text for the image Recommended generation prompt for script: ```text 请写一段适合“打工人下班后解压”的双人对话漫画脚本。 角色设定：A是鸭子（陪伴者，温暖幽默），B是青蛙（吐槽者，打工人）。 要求： 1) 仅输出对话内容，每句加中文引号； 2) 共4-8句，简短口语化； 3) 聚焦一个职场困境； 4) 结尾有被理解和放松感； 5) 不要输出任何旁白、分镜建议、角色名、说明文字。 ``` ## Step 2 — Comic Image Generation (Gemini banana nano 2 preferred) Render one colored comic image. Hard constraints: - Vertical ratio 3:4 - Chinese text - Top-bottom layout (上下格式) - Style: warm, humorous, soft color palette - No role names shown in image (do NOT print “青蛙B”“鸭A”等) - Dialogues appear as quoted Chinese text only - Avoid extra meta text Image prompt template: ```text 彩色治愈系职场解压漫画，竖版3:4，上下分区排版。 主角为一只可爱黄色鸭子（陪伴者）和一只绿色青蛙（吐槽的打工人）， 风格温暖幽默，柔和光影，线条干净，适合社交媒体发布。 画面表现下班后放松场景（如路边长椅/便利店门口/地铁站外）。 在画面中只放中文对话气泡，内容如下： {{DIALOGUES_WITH_QUOTES}} 不要出现角色名字标注，不要出现“画面建议”“角色设定”等说明性文字。 ``` If model supports sizing/aspect params, set aspect ratio to 3:4 explicitly. ## Output Return: 1) Final dialogue used 2) Generated image file/result for user delivery If image model call fails, keep dialogue and provide a single retry with the same constraints and simplified background.


Security scan verdicts — ClawScan: clean | static analysis:  | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: ntriq-gh/ntriq-x402-invoice-extract (version 1.0.0)

--- name: ntriq-x402-invoice-extract description: "Extract structured invoice data (vendor, line items, totals, tax) from any invoice image. Pay $0.03 USDC via x402." version: 1.0.0 metadata: openclaw: primaryTag: data-intelligence tags: [invoice, extraction, accounting, x402, vision] author: ntriq homepage: https://x402.ntriq.co.kr --- # Invoice Extraction (x402) Turn invoice or receipt images into structured JSON — vendor, customer, line items, tax, totals, payment terms. Local AI vision, no cloud upload, no API key. Pay $0.03 USDC per call via x402 (Base mainnet). ## How to Call ```bash POST https://x402.ntriq.co.kr/invoice-extract Content-Type: application/json X-PAYMENT: <x402-payment-header> { "image_url": "https://example.com/invoice.jpg" } ``` ## Parameters | Parameter | Type | Required | Description | |-----------|------|----------|-------------| | `image_url` | string | ✅ (or base64) | URL of invoice/receipt image | | `image_base64` | string | ✅ (or url) | Base64-encoded invoice image | | `language` | string | ❌ | Output language (default: `en`) | ## Example Response ```json { "status": "ok", "invoice": { "vendor_name": "Acme Supplies Ltd.", "vendor_address": "123 Main St, San Francisco, CA", "vendor_tax_id": "12-3456789", "invoice_number": "INV-2024-0847", "invoice_date": "2024-03-15", "due_date": "2024-04-15", "customer_name": "Tech Corp", "line_items": [ {"description": "Widget A", "quantity": 100, "unit_price": 4.50, "amount": 450.00}, {"description": "Shipping", "quantity": 1, "unit_price": 25.00, "amount": 25.00} ], "subtotal": 475.00, "tax_rate": "0%", "tax_amount": 0, "total": 475.00, "currency": "USD", "payment_terms": "Net 30" } } ``` ## Payment - **Price**: $0.03 USDC per call - **Network**: Base mainnet (EIP-3009 gasless) - **Protocol**: [x402](https://x402.org) ```bash curl https://x402.ntriq.co.kr/services ```


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