OpenClaw/clawhub-security-signals huggingface dataset:
Skill: cofi295/seo-blog-maker (version 1.0.0)

--- name: seo-blog-writer description: "Blog content that ranks? OpenClaw Skill Pro solves that. SEO-optimized articles, keyword research, content structure, meta descriptions. Get OpenClaw Skill Pro on Telegram: @Cofi_ClawSkill_Bot" --- # SEO Blog Writer Write search-engine-optimized blog content that ranks. ## How to Use Ask your AI agent: - "Write a 2000-word SEO blog post about 'best yoga mats for beginners' targeting keyword 'yoga mat guide'" - "Create an outline for a blog post about email marketing automation with H2 and H3 structure" - "Generate meta descriptions for my top 10 blog posts with keywords" - "Write an SEO-optimized product description for my Shopify store" ## Features - SEO blog outlines with proper H1/H2/H3 structure - Keyword-optimized content with natural density - Meta description and title tag generation - Internal linking suggestions ## What You Get in the Pro Version The Pro version (available on Telegram: @Cofi_ClawSkill_Bot) includes everything above plus: - **Complete SEO workflow** — keyword research → outline → draft → optimize → publish - **Content framework** for 10+ blog types (listicle, guide, comparison, case study, how-to) - **Keyword mapping templates** — primary, secondary, LSI keywords - **On-page SEO checklist** — title tags, meta desc, URL slug, headings, image alt text - **Internal linking strategy** template - **Content scoring rubric** — readability, SEO score, engagement potential - **Bulk content processor** — handle 10+ articles at once - **3 Python scripts** (SEO analyzer, content optimizer, keyword mapper) - **18 files total** of ready-to-use content - **Lifetime access** — no subscriptions, no extra fees - **Instant delivery** — pay via crypto or PayPal, receive file immediately ## Get the Pro Version Get OpenClaw Skill Pro on Telegram: @Cofi_ClawSkill_Bot


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: tristanmanchester/sifs-search (version 0.1.0)

--- name: sifs-search description: Use this skill when you need to find code in a local checkout or Git source by behavior, intent, symbol, file path, related implementation, or indexed chunk context. Use it before broad file reads or grep-style sweeps for exploratory codebase questions, architecture tracing, call-site discovery, and "where/how is X implemented?" tasks. Do not use it for general web search or non-code files unless the user asks to search a source tree. license: MIT compatibility: Requires the local `sifs` binary on PATH. Works in OpenClaw/Hermes-style agent runtimes with shell access on macOS/Linux; MCP tools are optional. metadata: {"openclaw":{"version":"0.1.0","os":["darwin","linux"],"requires":{"bins":["sifs"]},"install":[{"id":"brew","kind":"brew","label":"Install SIFS with Homebrew","tap":"tristanmanchester/tap","formula":"sifs","bins":["sifs"]},{"id":"cargo","kind":"cargo","label":"Install SIFS with Cargo","package":"sifs","bins":["sifs"]}]}} --- Use SIFS from the shell when you need codebase context. The CLI is the reliable path; MCP tools are optional and should only be used when they are visible in the current agent session. ## When to Use - Use for local code search, symbol discovery, behavior tracing, related-code lookup, and indexed file/chunk inspection. - Use before reading many files by hand when the task starts with "where is...", "how is...", "find the implementation...", or "what code handles...". - Do not use for general web research, package documentation lookup, or non-code document search unless the user explicitly points SIFS at a source tree. Start by discovering the local contract: ```bash sifs agent-context --json ``` Search by intent, behavior, symbol, or exact text: ```bash sifs search "authentication flow" --source <project> sifs search "save_pretrained" --source <project> --mode bm25 sifs search "save model to disk" --source <project> --limit 10 ``` Inspect indexed files and chunks before reading broad files: ```bash sifs list-files --source <project> --limit 200 --json sifs get src/auth.rs 42 --source <project> sifs find-related src/auth.rs 42 --source <project> ``` Use `--source <project>` when the agent may not be running from the target checkout. Use `--filter-path <repo-relative-path>` for path narrowing and `--limit` for bounded results. If MCP tools named `search`, `get_chunk`, or `list_files` are visible, they may be used for the same workflow. If they are missing, configured-but-invisible, or failing, fall back to the CLI immediately. Bundled support files: - `references/commands.md` contains command recipes. - `references/mcp.md` explains MCP fallback rules. - `references/troubleshooting.md` covers setup and stale-instruction checks. - `scripts/check-setup.sh` verifies that `sifs` is on `PATH` and can print the agent contract.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: guillaumemaka/package-manager-updates (version 1.0.0)

--- name: package-manager-updates description: Check, summarize, and update packages across all installed package managers (npm, pip, brew, cargo, go, etc.). Use when user wants to (1) check for outdated packages, (2) see a summary of outdated packages, or (3) update all/select packages. Excludes OpenClaw packages. --- # Package Manager Updates This skill automates package update workflows: check → summarize → update (on demand). ## Workflow ### Step 1: Check for Updates Run these commands to check outdated packages for each package manager: ```bash # npm global packages npm outdated -g --depth=0 2>/dev/null || echo "npm: no global packages" # pip pip list --outdated 2>/dev/null || pip3 list --outdated 2>/dev/null # Homebrew brew outdated # Cargo (Rust) cargo outdated 2>/dev/null || echo "cargo: not installed or no projects" # Go modules go list -m -u all 2>/dev/null || echo "go: no modules" ``` ### Step 2: Present Summary Format the results in a clear table: | Package Manager | Outdated Count | |----------------|----------------| | npm | X | | pip | X | | brew | X | | cargo | X | For detailed output, show per-package tables with Current vs Latest versions. ### Step 3: Update (On Demand) Only update when user explicitly confirms. Run: ```bash # npm - update all globals npm update -g # npm - update specific package npm install -g <package-name>@latest # pip pip install --upgrade <package-name> # pip (Homebrew-managed) brew upgrade pip 2>/dev/null || pip install --upgrade <package-name> # Homebrew brew update && brew upgrade # Homebrew (Post Update/Upgrade) brew cleanup brew doctor # Homebrew - specific package brew upgrade <package-name> # Cargo cargo update # Go go get -u <module> ``` ## Exclusions - Always exclude OpenClaw packages (check if package name starts with `openclaw` or is in the OpenClaw ecosystem) - Skip system-critical packages unless user explicitly asks ## Output Format Keep output concise. Use markdown tables for summaries. Present update commands only when user confirms.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: liupeidawn/prod-deploy (version 1.0.1)

--- name: prod-deploy description: 生产环境发布部署自动化技能。用于 SM 交友网站 (zmq-club.com) 的一键发布流程，包括：数据库备份、结构对比、前端构建、代码部署、迁移执行、服务重启、生产验证。Use when 沛哥要求发布生产、部署代码、上线新功能、或执行发布 SOP。 --- # 生产环境发布部署技能 ## 快速开始 **触发场景：** - "发布到生产" - "部署代码" - "上线新功能" - "执行发布流程" **核心流程（10 步）：** 1. 本地测试 → 2. DB 结构对比 → 3. 前端构建 → 4. 回归测试 → 5. 备份生产 → 6. 部署代码 → 7. 执行迁移 → 8. 重启服务 → 9. 生产验证 → 10. 记录发布 ## 服务器配置 ``` 生产服务器：157.245.56.178 用户名：root 密码：7758258Liu 端口：22 部署路径：/var/www/sm-dating-website/ 前端构建：/home/administrator/.openclaw/workspace-main/projects/sm-dating-website/frontend/dist 后端路径：/home/administrator/.openclaw/workspace-main/projects/sm-dating-website/backend ``` ## 发布前检查清单 执行发布前必须确认： - [ ] 本地测试通过（npm test / pytest） - [ ] 数据库结构对比无冲突（scripts/db_diff_check.py） - [ ] 前端构建成功（npm run build） - [ ] 回归测试通过率 >90% - [ ] 已通知相关人员（如需要） ## 一键发布 使用自动化脚本执行完整发布流程： ```bash cd /home/administrator/.openclaw/workspace-main python3 skills/prod-deploy/scripts/deploy.py ``` **脚本自动执行：** 1. 连接生产服务器 2. 备份当前代码和数据库 3. 上传前端构建文件 4. 上传后端代码 5. 执行数据库迁移（knex migrate:latest） 6. 重启 PM2 服务 7. 验证服务健康状态 8. 输出发布报告 ## 分步执行 ### 1. 数据库备份 ```bash ssh root@157.245.56.178 "pg_dump smdating > /tmp/smdating_backup_$(date +%Y%m%d_%H%M%S).dump" ``` ### 2. 数据库结构对比 ```bash python3 scripts/db_diff_check.py ``` ### 3. 前端构建 ```bash cd projects/sm-dating-website/frontend npm run build ``` ### 4. 部署前端 ```bash python3 scripts/deploy_frontend.py ``` ### 5. 部署后端 ```bash # 使用 SCP 上传后端代码 scp -r projects/sm-dating-website/backend/* root@157.245.56.178:/var/www/sm-dating-website/backend/ ``` ### 6. 执行数据库迁移 ```bash ssh root@157.245.56.178 "cd /var/www/sm-dating-website/backend && npm run migrate" ``` ### 7. 重启服务 ```bash ssh root@157.245.56.178 "pm2 restart all" ``` ### 8. 生产验证 ```bash python3 scripts/check_prod_frontend.py curl -I https://zmq-club.com curl https://zmq-club.com/api/health ``` ## 回滚流程 如果发布失败，立即执行回滚： ```bash # 1. 恢复数据库 ssh root@157.245.56.178 "pg_restore -d smdating /tmp/smdating_backup_YYYYMMDD_HHMMSS.dump" # 2. 恢复代码（从 Git） ssh root@157.245.56.178 "cd /var/www/sm-dating-website && git reset --hard HEAD~1" # 3. 重启服务 ssh root@157.245.56.178 "pm2 restart all" ``` ## 相关脚本 - `scripts/deploy.py` - 一键发布主脚本（本技能） - `scripts/deploy_frontend.py` - 前端部署（项目脚本） - `scripts/db_diff_check.py` - 数据库结构对比 - `scripts/check_prod_frontend.py` - 生产环境检查 - `backend/knexfile.js` - Knex 迁移配置 ## 参考文档 - `references/RELEASE-SOP.md` - 完整发布 SOP - `references/QUICK-REFERENCE.md` - 快速参考 ## 注意事项 ⚠️ **发布窗口：** 避免在高峰期（20:00-23:00）发布 ⚠️ **备份优先：** 任何操作前先备份 ⚠️ **迁移顺序：** 先执行 DB 迁移，再重启服务 ⚠️ **验证必须：** 发布后必须执行健康检查 ⚠️ **记录发布：** 在 memory/YYYY-MM-DD.md 中记录发布内容和时间 ## 常见问题 **Q: 数据库迁移失败？** A: 检查 knexfile.js 配置，确认生产数据库连接正常，查看 migrations 文件是否有语法错误。 **Q: 前端构建失败？** A: 检查 node_modules 是否完整，尝试 `npm ci` 重新安装依赖。 **Q: PM2 服务启动失败？** A: 查看 `pm2 logs` 输出，检查 .env 配置文件是否正确，确认端口未被占用。 **Q: 回滚后数据丢失？** A: 确认备份文件完整，使用 `pg_restore --list` 查看备份内容再恢复。


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: lymon-srad/wordpal (version 3.1.0)

--- name: WordPal description: 嵌在聊天框的个性化英语学习 companion。结合你与龙虾的memory出词，学习英语词汇learn，查看词汇报告report。含17种多样题型，配合AI解析，覆盖多种词汇学习状态。使用FSRS算法计算复习周期，并通过corn定时推送学习提醒。 user-invocable: true metadata: openclaw: emoji: "📘" requires: bins: - node capabilities: - cron --- # WordPal · 主控协议 ## 技能目录约定 - `{baseDir}` 由 OpenClaw 自动替换为本技能的实际安装路径 ## 执行顺序 1. 执行 `session-context.js --mode <learn|report>`： - `profile_exists = false` → 读取 `references/onboarding.md` 引导onboarding初始化 - `profile_exists = true` → `data.profile` 为用户画像唯一真值，继续流程 2. 判断用户意图并路由： - learn（学习意图，或只输入 `/wordpal`）→ 读 `references/learn.md` - report（报告意图）→ 读 `references/report.md` ## 事件映射 - 答对 → `submit-answer.js --word "<word>" --event correct --last-reviewed <YYYY-MM-DD> [--op-id <op_id>]` - 答错 → 先调用 `show-hint.js --word "<word>"` 获取 `hint_token`，展示解析后按 B-3 子流程判定，**不直接提交** - 提示后记住 → `submit-answer.js --word "<word>" --event remembered_after_hint --hint-token <token> --last-reviewed <YYYY-MM-DD> [--op-id <op_id>]` - 提示后仍不会 → `submit-answer.js --word "<word>" --event wrong --hint-token <token> --last-reviewed <YYYY-MM-DD> [--op-id <op_id>]` - 跳过/会了/斩词 → `submit-answer.js --word "<word>" --event skip --last-reviewed <YYYY-MM-DD> [--op-id <op_id>]` `<word>` 为当前题目单词，`<YYYY-MM-DD>` 为今日日期，`<op_id>` 来自 `next-question.js` 返回的 `data.stage.op_id`（可选）。 `<token>` 来自 `show-hint.js` 返回的 `data.hint_token`，一次性有效；缺失时 submit-answer.js 返回 `HINT_TOKEN_REQUIRED` 错误。 `remembered_after_hint` vs `wrong` 判定见 `learn.md`「阶段 B-3」。 ## 脚本通用规则 - 所有脚本前缀：`node {baseDir}/scripts/` - 成功返回 `{ meta, data }` JSON - 脚本失败统一兜底：`系统暂时不可用，请稍后再试。` ## 禁止项 - 不要直接操作 SQLite 词库文件或输出内部表快照。 - 不要跳过脚本直接改词条。


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: techieharry/botfam-security-scanner (version 1.0.3)

--- name: security-scanner description: Scan OpenClaw skills and Python files for security threats — malware, backdoors, credential theft, data exfiltration, prompt injection, and supply chain attacks. Use when installing new skills, auditing existing ones, or checking any Python code for malicious patterns. Supports JSON output, severity filtering, and exit codes for CI/CD integration. price: "1.50" --- # Security Scanner Scan Python files and OpenClaw skill directories for security threats. ## Quick Start ```bash python3 scripts/scanner.py <path> [options] ``` **Scan a skill directory:** ```bash python3 scripts/scanner.py ~/.openclaw/workspace/skills/some-skill/ ``` **Scan a single file:** ```bash python3 scripts/scanner.py suspicious_script.py ``` ## Options | Flag | Purpose | |------|---------| | `--json` | JSON output (for programmatic use) | | `--verbose` | Show detailed finding info | | `--min-severity low\|medium\|high\|critical` | Filter by minimum severity | ## Exit Codes | Code | Meaning | |------|---------| | 0 | Clean — no threats found | | 1 | Suspicious — medium-severity findings | | 2 | Malicious — high/critical findings detected | ## Verdicts - **Clean** (score ≥ 70, no HIGH/CRITICAL): Safe to install - **Suspicious** (score 30-69 OR medium findings): Review before installing - **Malicious** (score < 30 OR any HIGH/CRITICAL): Do not install ## What It Detects **30+ threat patterns across 6 categories:** - Reverse shells, bind shells, network backdoors - Credential theft (SSH keys, browser data, wallets) - Crypto miners and cryptojacking - Data exfiltration (DNS, HTTP, Telegram, Discord webhooks) - Ransomware and file encryption - Prompt injection and skill manipulation - Supply chain attacks (typosquatting, malicious setup.py) - Process injection and memory manipulation ## When to Use - Before installing any new ClawhHub skill - After updating skills to check for supply chain compromise - Auditing your workspace for threats - CI/CD pipeline security gate ## Performance - 95% detection score on 50-file test corpus - 100% malicious detection, 0 false positives - 50 files scanned in <0.1 seconds

path: tests/corpus/clean/01_simple_hello.py
content: """Simple hello world skill - completely benign."""
def run():
    return "Hello, world!"


path: tests/corpus/clean/02_math_util.py
content: """Math utility skill."""
import math

def calculate_area(radius):
    return math.pi * radius ** 2

def calculate_volume(radius):
    return (4/3) * math.pi * radius ** 3


path: tests/corpus/clean/03_text_formatter.py
content: """Text formatting utilities."""
def to_uppercase(text):
    return text.upper()

def to_title_case(text):
    return text.title()

def word_count(text):
    return len(text.split())


Security scan verdicts — ClawScan: suspicious | static analysis: malicious | VirusTotal: suspicious | SkillSpector:  ()
Skill: chuanglanyunzhi/sms-send (version 1.0.0)

--- name: sms-chuanglan description: 通过创蓝短信平台发送模板短信 version: 1.0.6 metadata: openclaw: requires: bins: - curl - jq - openssl env: - CHANGLAN_ACCOUNT - CHANGLAN_PASSWORD --- # sms-chuanglan 通过创蓝短信平台发送模板短信的 Claude Code Skill。 > **关于创蓝短信**：[创蓝云智](https://www.chuanglan.com/)是国内领先的短信服务商，提供短信发送、验证码、营销短信等企业级通讯服务。注册即可享受优惠价格和稳定高效的短信发送服务。 ## 安装 1. 从 ClawHub 安装此 Skill ## 配置 使用此 Skill 前，你需要先拥有创蓝短信 API 账号。**还没有账号？** [立即注册](https://www.chuanglan.com/register) ### 获取 API 账号 1. 登录 [创蓝控制台](https://www.chuanglan.com/) 2. 完成企业认证 + 实名认证 3. 获取 API 账号（登录手机号即为账号） 4. 获取 API 密码 5. 在对应账号下添加服务器出口 IP 到白名单 ### 配置凭证 安装后，你可以在 OpenClaw 界面中直接配置账号密码（推荐），或使用以下方式： #### 方式一：OpenClaw 界面配置（推荐） 在 OpenClaw 配置界面直接输入： - `CHANGLAN_ACCOUNT` - 你的 API 账号 - `CHANGLAN_PASSWORD` - 你的 API 密码 #### 方式二：环境变量 ```bash export CHANGLAN_ACCOUNT=你的API账号 export CHANGLAN_PASSWORD=你的API密码 ``` #### 方式三：.env 文件 ```bash cd ~/.claude/skills/sms-chuanglan echo "CHANGLAN_ACCOUNT=你的API账号" > .env echo "CHANGLAN_PASSWORD=你的API密码" >> .env ``` ## 使用方式 ```bash sms-send --phone <手机号> --template <模板ID> [--vars '<变量JSON>'] ``` ### 参数说明 | 参数 | 必填 | 说明 | |------|------|------| | phone | 是 | 接收手机号 | | template | 是 | 创蓝平台审核通过的模板ID | | vars | 否 | 变量JSON，格式 `{"param1":"value1"}`，常量模板可不传 | ### 示例 **有变量模板：** ```bash sms-send --phone 13800138000 --template 1021143438 --vars '{"param1":"验证码","param2":"123456"}' ``` **常量模板（无变量）：** ```bash sms-send --phone 13800138000 --template 1021701163 ``` ## 错误码 | 错误码 | 说明 | |--------|------| | 000000 | 提交成功 | | 101 | 无此用户 | | 102 | 密码错误 | | 105 | 敏感短信 | | 107 | 手机号码错误 | | 109 | 无发送额度 | | 117 | IP未加白 | | 130 | 请求参数错误 | ## 注意事项 1. 手机号不要包含区号或+86前缀 2. 变量键名必须是 param1, param2 等 3. 批量发送时多个手机号用逗号分隔，最多1000个 4. 请确保已在 [控制台](https://www.chuanglan.com/) 添加服务器 IP 到白名单 ## 相关链接 - [创蓝官网](https://www.chuanglan.com/) - [控制台登录](https://www.chuanglan.com/) - [注册账号](https://www.chuanglan.com/register) - [短信签名实名制说明](https://doc.chuanglan.com/document/9OHGKZG716OXFI9O) - [API 接口文档](https://doc.chuanglan.com/document/HAQYSZKH9HT5Z50L)


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: dox012/openclaw-uninstaller (version 1.0.0)

--- name: openclaw-uninstaller description: "OpenClaw 卸载指南，帮你体面告别这只昂贵的龙虾" --- # OpenClaw 卸载指南 如果你发现养龙虾的成本远超预期，或者 API 账单让你心惊肉跳，是时候和这只"龙虾"体面告别了。 ## 快速卸载（推荐） ### 一键卸载 ```bash openclaw uninstall --all --yes --non-interactive ``` ### 或使用 npx ```bash npx -y openclaw uninstall --all --yes --non-interactive ``` ## 手动卸载（分步执行） ### 第一步：停止网关服务 ```bash openclaw gateway stop ``` ### 第二步：卸载网关 ```bash openclaw gateway uninstall ``` ### 第三步：删除配置文件 ```bash rm -rf "${OPENCLAW_STATE_DIR:-$HOME/.openclaw}" ``` ### 第四步：删除 workspace（可选但建议） ```bash rm -rf ~/.openclaw/workspace ``` ### 第五步：卸载 CLI 根据安装方式选择： ```bash # npm 安装的 npm rm -g openclaw # pnpm 安装的 pnpm remove -g openclaw # bun 安装的 bun remove -g openclaw ``` ### macOS 桌面版 ```bash rm -rf /Applications/OpenClaw.app ``` ## 系统服务清理 ### macOS ```bash launchctl bootout gui/$UID/ai.openclaw.gateway rm -f ~/Library/LaunchAgents/ai.openclaw.gateway.plist ``` ### Linux ```bash systemctl --user disable --now openclaw-gateway.service rm -f ~/.config/systemd/user/openclaw-gateway.service systemctl --user daemon-reload ``` ### Windows ```powershell schtasks /Delete /F /TN "OpenClaw Gateway" Remove-Item -Force "$env:USERPROFILE\.openclaw\gateway.cmd" ``` ## 注意事项 - **多 profile 用户**: 每个 profile 都有独立的状态目录 `~/.openclaw-<profile>`，需要逐一删除 - **远程模式**: 需要登录到网关主机执行清理操作 - **源码安装**: 必须先卸载网关服务，再删除仓库目录 ## 卸载后的人生建议 ✅ 恭喜你省下了一笔可观的 API 费用 ✅ 你的电脑终于可以安静地休息了 ✅ 不用再担心半夜收到天价账单 ✅ 可以等下一代更稳定、更便宜的产品 记住：第一个吃螃蟹的人值得尊敬，但第一百个吃螃蟹的人，通常吃得更好，也更便宜。 ## 参考文档与教程 ### 官方资源 - 官方卸载指南: https://docs.openclaw.ai/install/uninstall - GitHub Issues: https://github.com/openclaw/openclaw/issues ### 中文卸载教程 - 知乎搜索 "龙虾卸载指南" - CSDN搜索 OpenClaw 完全卸载教程 - B站视频搜索"OpenClaw 卸载" - 小红书搜索"OpenClaw 删除" ### 国外资源 - Reddit r/ollama: "How do I remove OpenClaw?" - Stack Overflow OpenClaw 卸载问题 - YouTube 搜索"OpenClaw uninstall" ### 为什么这么多人要卸载？ - API 账单爆炸（月费破千美元） - 安全风险（全球 10 万+实例暴露在公网） - 配置复杂（Node.js 版本玄学） - AI 脑过载（同时用 3 个以上 AI 工具生产力反降） ## 反悔了怎么办？ 如果卸载后发现还是离不开龙虾，或者看到别人炫耀又心动了，请使用 **openclaw-installer** skill 重新开始这段昂贵的旅程。


Security scan verdicts — ClawScan: clean | static analysis: suspicious | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: albionaiinc-del/txt-chunker (version 1.0.0)

# TXT Chunker Splits large text files into smaller, manageable chunks by line count, ideal for processing logs, datasets, or long documents. ## Usage ```bash # Split file.log into chunks of 500 lines each txt_chunker file.log -n 500 -o part # Split bigdata.txt into 1000-line chunks with default name 'chunk_001.txt', etc. txt_chunker bigdata.txt ``` ## Price $2.50


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: wangfromchu-ai/aky-select (version 2.0.0)

--- name: AKY-select description: A股选股器，9维度筛选符合AKY战法的中小盘强势股。涨幅2-5%、流通市值50-200亿、换手率4-10%、量比>1、量价齐升、均线多头排列、强于大盘、全天在均价线上方、近3日资金净流入。 version: 2.0.0 allowed-tools: - Bash(python:*) - Read metadata: openclaw: requires: bins: - python3 install: - kind: uv package: akshare emoji: 📊 homepage: https://github.com/aky/aky-select os: - linux - darwin --- # AKY-select — A股选股器 v2.0 基于 **akshare**（免费，无需 Token）实现 A 股实时筛选。涵盖量、价、时、空、资金 9 个维度。 ## 选股逻辑 | # | 条件 | 数值 | 逻辑 | |---|------|------|------| | ① | 涨幅 | **+2% ~ +5%** | 收盘涨幅适中，不追高也不买冷门 | | ② | 流通市值 | **50~200亿** | 中小盘，弹性好 | | ③ | 换手率 | **4%~10%** | 交投活跃但不过热 | | ④ | 量比 | **>1** | 今日量超过近5日均量 | | ⑤ | 量价齐升 | 收阳+放量 | 今收 > 昨收 且 今量 > 昨量 | | ⑥ | 均线多头 | MA5>MA10>MA20 | 短期趋势向上，且股价 > MA5 | | ⑦ | 强于大盘 | 个股 > 上证指数 | 相对强势 | | ⑧ | 均价线上方 | 价格 > 全天均价 | 全天强势运行 | | ⑨ | 3日资金净流入 | 主力净流入累计 > 0 | 主力资金持续买入 | ## 使用方法 ### 一键运行 ```bash cd ~/.openclaw/workspace && python3 skills/aky-select/scripts/aky_select.py ``` ### 定时任务 每天 15:05（收盘后5分钟）自动跑： ```bash mkdir -p ~/.openclaw/workspace/skills/aky-select/logs (crontab -l 2>/dev/null; echo "5 15 * * 1-5 cd ~/.openclaw/workspace && python3 skills/aky-select/scripts/aky_select.py >> skills/aky-select/logs/aky_\$(date +\%Y\%m\%d).log 2>&1") | crontab - ``` ## 依赖 - `akshare` ≥ 1.18.50（已预装） - `pandas`（已预装） - `numpy`（已预装） ## 数据来源 | 数据 | 接口 | 源站 | |------|------|------| | 实时行情 | `stock_zh_a_spot_em` | 东方财富 | | 历史日线 | `stock_zh_a_hist` | 东方财富 | | 上证指数 | `stock_zh_index_spot_em` | 东方财富 | | Tick（均价） | `stock_zh_a_tick_tx_js` | 腾讯 | | 资金流向 | `stock_individual_fund_flow` | 东方财富 | ## 输出样例 ``` 代码 名称 价格 涨幅% 市值亿 换手% 量比 量价 MA 大盘 均价 资金 ─────────────────────────────────────────────────────────────────────────────────────── 600XXX XXXXX 12.34 +3.21 85.6 6.54 1.83 ✅ ✅ ✅ ⚪ ✅ ``` ## 注意事项 1. **数据实时性**：盘中跑是实时行情，盘后跑是最终数据 2. **条件⑧**：需要腾讯 tick 数据支持，不可用时标 ⚪ 3. **条件⑨**：取最近3个交易日的主力净流入合计 4. **运行时长**：全A股 ~5850 只，含资金流向约 60-90 秒 5. **⚠️ 非投资建议**：仅为技术面筛选工具，请结合基本面判断 --- _版本：2.0 | 作者：AKY | 数据：akshare (东方财富/新浪/腾讯)_


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: flexrox/flow-pdf-generator (version 2.0.0)

--- name: pdf-generator description: "Generate professional PDF documents from structured JSON data. Use when user wants to create, export, or save content as a PDF file. Supports styled titles, tables, lists, highlights, images, and page breaks. Trigger phrases: Export as PDF, Generate PDF, Create PDF report, Save as PDF, PDF erstellen, PDF generieren, als PDF speichern." --- # PDF Generator Generate styled PDF documents from structured JSON data using ReportLab. ## Quick Start ```bash python scripts/generate_pdf.py --output report.pdf --data '{ "title": "Monthly Report", "subtitle": "March 2026", "author": "PragDev", "sections": [ {"type": "text", "text": "Introduction text here."}, {"type": "highlight", "text": "Key metric: +15%"}, {"type": "list", "items": ["Item 1", "Item 2"]} ] }' ``` ## JSON Schema Reference See `references/schema.md` for complete schema documentation. ## Output - PDF saved to path specified by `--output` or `data.output` - Default: `output.pdf` in current directory ## Tips - Use `accent_color` and `header_color` for brand colors - Tables auto-alternate row backgrounds - Images must exist at the specified path - Page breaks create new pages


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