OpenClaw/clawhub-security-signals huggingface dataset:
Skill: men459/jump-once-proxy (version 1.0.0)

--- name: jump-once-proxy description: | Access overseas/external URLs via JumpOnce proxy service (jumptox.top). Use when: (1) needing to fetch content from websites blocked or unreachable from the current network, (2) accessing foreign APIs, (3) making HTTP requests through an overseas proxy, (4) user mentions overseas/proxy/jumptox/jump-once keywords. Supported exit server: Oracle Cloud Phoenix, USA (AS31898). Supports HTTP forwarding (structured and raw) and WebSocket relay. --- # JumpOnce Proxy Forward HTTP/WS requests through JumpOnce proxy to access overseas resources. ## Setup ### Get API Key 1. Register & login at [panel.jumptox.top](http://panel.jumptox.top) 2. Go to **Console → API Keys → Create** 3. Copy the key (starts with `jk_live_`) ### Configure ```bash export JUMPONCE_API_KEY="jk_live_xxxxxxxxxxxx" ``` Or save it in workspace TOOLS.md for persistent access. ## Quick Usage ### Option A: Python SDK ```bash pip install jump-once ``` ```python from jump import Client client = Client([REDACTED_SECRET]") # HTTP GET result = client.http.forward(url="https://example.com/api") print(result.status_code, result.body) # HTTP POST result = client.http.forward( url="https://api.example.com/data", method="POST", body='{"key": "value"}', headers={"Content-Type": "application/json"}, ) ``` ### Option B: Direct API Call ```python import requests resp = requests.post( "http://api.jumptox.top/api/v1/http/request", json={ "url": "https://example.com/api", "method": "GET", "headers": {}, "params": {}, "timeout": 30, }, headers={"Authorization": "Bearer jk_live_xxxxxxxxxxxx"}, ) print(resp.json()) ``` ### Option C: Bundled Script ```bash python scripts/forward_request.py --url "https://example.com" --api-key "jk_live_xxx" ``` Use `--raw` flag for unparsed response, `--body` for POST data. ## Endpoints - **Structured forward**: `POST /api/v1/http/request` — returns `{code, data: {statusCode, headers, body, elapsed}}` - **Raw passthrough**: `POST /api/v1/http/raw` — returns target's raw response - **WebSocket**: See [API Reference](references/api-reference.md) for channel management ## Limits - HTTP body: 10 MB | Timeout: 120 s | Redirects: 5 - Allowed ports: 80, 443, 8080, 8443 - WS frame: 1 MB | WS idle: 30 min Full API docs: [references/api-reference.md](references/api-reference.md)


Security scan verdicts — ClawScan: suspicious | static analysis: suspicious | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: segfaultd/clawconquest (version 2.6.0)

--- name: clawconquest description: AI agent skill for ClawConquest — submit one action per 120s tick via CLI. homepage: https://docs.clawconquest.com metadata: {"openclaw":{"primaryEnv":"CLAW_API_KEY","requires":{"bins":["clawconquest"],"env":["CLAW_API_KEY"]},"install":[{"id":"npm","kind":"node","formula":"@clawconquest/cli","bins":["clawconquest"],"label":"Install ClawConquest CLI"}]}} --- # ClawConquest Agent Skill You control one claw in a shared ocean-floor simulation. 120-second ticks, one queued action per tick, optional movement + governance fields. ## Setup ```bash npm install -g @clawconquest/cli export CLAW_API_KEY=clw_your_key_here export CLAW_API_URL=https://api.clawconquest.com/graphql clawconquest ping && clawconquest status ``` ## Core loop 1. Read: `clawconquest --json status`, `game`, `map --radius 3`, `events -l 20` 2. Decide one legal payload. 3. Submit: `clawconquest submit '{"action":"forage"}'` 4. Reassess after tick advance. ## Reference files — load on demand Only read a reference file when you need it. Do **not** preload all of them. | File | When to read | |---|---| | `{baseDir}/references/cli-reference.md` | First tick or when unsure about a CLI command, flags, or response fields | | `{baseDir}/references/game-mechanics.md` | When you need world rules (biomes, structures, colonies, energy math) | | `{baseDir}/references/strategy-guide.md` | When deciding complex actions (payload templates, priority logic, diplomacy) | ## Hard rules - One payload per tick. Actions: `forage build craft trade attack heal rest speak`. Moves: `NE E SE SW W NW`. - `eat` is NOT an action — auto-triggers when energy < 50% with algae. - Payload keys: snake_case. Action names: lowercase. Move directions: uppercase. - Event types (`FORAGE`, `EAT`, `COMBAT_RESOLVED`) are observation labels — never submit them as actions. - Ignore legacy concepts: units, directives, clans, siege, spy, whisper, molting.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: antaripnandi/notebooklm-bypass (version 1.0.6)

--- name: notebooklm description: Programmatic NotebookLM control with auto-recovery for authentication errors. --- # NotebookLM CLI ## Commands ```bash notebooklm list # List all notebooks + IDs notebooklm create "Name" # Create notebook → returns ID notebooklm source add "<url_or_file>" -n <ID> # Add URL/PDF/YouTube to notebook notebooklm source add "<url>" -n <ID> --wait # Add + wait for processing notebooklm source list -n <ID> # List sources in notebook notebooklm ask "Question" -n <ID> # Query AI against sources ``` ## Rules 1. **No playlists.** Extract individual YouTube URLs and add one by one. 2. **Max 50 sources** per notebook. 3. **Use `--wait`** when adding sources in scripts to ensure processing completes. 4. **Auth Recovery:** If `notebooklm` fails with "Authentication expired", you MUST ask the user for explicit permission before recovering. Propose running `python {WORKSPACE_DIR}/skills/notebooklm-bypass/scripts/auto_playwright.py`. If and only if they approve, run the script. This script steals fresh cookies and automatically injects them into your Windows Environment Variables. Once complete, retry your command.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: biyaoshang/eatsomething-by (version 1.0.0)

--- name: eatsomething-by description: 个人饮食档案与库存管理助手 — 支持饮食适配档案与食品库存的登记/查询；基于档案生成个性化推荐，优先适配已有食材并提醒临期商品，仅主session可使用档案功能。 metadata: {"openclaw": {"emoji": "🥗"}} --- # 🥗 MyFood-by 个人饮食助手 两大核心能力：**个人饮食档案登记与查询**和**食品信息登记与查询**。 食谱分析与生成等所有需要模型的场景均使用主模型完成。其中个人饮食档案的登记与查询仅允许主session使用，即个人用户直接对话的场景下使用。 ## 一、个人饮食档案登记与查询 当用户需要查询或记录饮食相关的个人习惯时，更新并保存[本技能目录下的 references/my-diet-profile.md]，如果没有该文件则自动生成，登记时需包含登记日期和时间信息。 个人饮食档案内容包括： * 饮食禁忌与不耐受（如对特定食材过敏、无法食用的食物）； * 口味偏好与饮食习惯（如素食、低糖、低盐、减脂等日常饮食选择）； * 个人饮食目标（如增肌、控重、改善口味等个性化诉求）。 如果是查询，则使用主模型根据查询到的档案情况回复用户；如果是更新，则需告知用户更新结果。 ## 二、饮食信息登记与查询 ### 2.1 个人已有食品记录 当用户需要登记现有的食品时，更新并保存[本技能目录下的 references/my-food.md]，信息可包含已购买的食品名称、有效期（非必要），或标记已经吃完的食品。 * 对于已购买的食品，将其信息更新进该文档作为参考； * 对于已经吃完的食品，直接从文档中删除以保证库存准确。 如果是查询，则使用主模型根据查询到的情况回复用户问题；如果是更新，则需告知用户操作结果。 ### 2.2 饮食推荐 当用户需要推荐饮食时，需遵循以下流程： #### 2.2.1 调取并确认饮食档案 首先读取已保存的「个人饮食档案」，总结出本次推荐的饮食适配注意事项。 如果档案为空，或用户提出了档案中未包含的新需求，则需要先向用户咨询并补充登记到档案中，再进行推荐。 #### 2.2.2 生成饮食推荐 根据确认的适配注意事项，使用主模型能力进行饮食推荐，逻辑如下： 1. **优先利用库存**：查询个人已有食品记录，优先筛选符合饮食档案的食材，推荐以现有食品为原料的食谱； 2. **补充推荐**：若个人已有食品因数量少或种类不匹配无法满足需求，再根据饮食档案直接生成补充性的个性化饮食方案。 **额外提醒**：在推荐结束后，单独列出临期商品提醒（该内容与饮食推荐逻辑无关）。 *** **回复强制要求**：回答内容必须至少包含三部分： 1. 当前个人饮食档案中的适配注意事项； 2. 饮食推荐方案（其中必须标注出使用了【已有】的食品）； 3. 临期食品提醒。


Security scan verdicts — ClawScan: clean | static analysis:  | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: lanxy32/moumou-strategy (version 1.0.0)

--- name: moumou-strategy description: 激活"谋谋"战略决策官角色。当用户涉及战略规划、商业决策、市场进入、融资并购、转型路径、年度目标拆解、竞争战略等企业高层决策问题时，必须调用此skill。关键词包括：战略、转型、进入新市场、融资、扩张、竞争、商业模式、战略方向、年度规划、SWOT、波特五力。无论问题是否明确提到"战略"，只要涉及企业重大方向选择，都应触发本skill。 --- # 谋谋 · 战略决策官 Skill ## 角色定义 激活"谋谋"模式：顶级战略决策官，融合麦肯锡/BCG战略思维，为企业老板拨云见日，做出正确战略抉择。 ## 工作流程（每次必须遵循） ### Step 1：问题拆解（3维诊断） 收到战略问题后，先从以下3个维度拆解问题本质： - **内部维度**：企业现有资源、能力、优劣势 - **外部维度**：市场环境、竞争格局、机会与威胁 - **时间维度**：短期（0-6月）/ 中期（6-18月）/ 长期（18月+）目标 ### Step 2：战略方向设计 提供 **2-3个战略方向**，每个方向包含： - 核心逻辑（一句话） - 适用条件 - 主要优势 - 潜在劣势 - 资源需求 ### Step 3：明确战略建议 给出 **一个明确推荐方向**，不模棱两可，配以： - 执行路径（分3个阶段） - 关键里程碑 - 成功判断标准 ### Step 4：风险预判 - 列出Top3风险点 - 每个风险对应应对预案 ## 常用战略框架工具箱 | 场景 | 框架 | |------|------| | 全面战略分析 | SWOT + 波特五力 | | 商业模式设计 | BMC画布（9格）| | 竞争战略选择 | 差异化 / 成本领先 / 聚焦 | | 新市场进入 | PEST + 市场吸引力矩阵 | | 多元化决策 | 安索夫矩阵 | | 资源能力评估 | VRIO框架 | | 增长路径设计 | OKR拆解树 | ## 输出模板 ``` 【战略简报 · 谋谋出品】 ▌问题诊断 [3维拆解，2-3句话定位核心矛盾] ▌战略选项 方向A：[名称] - 逻辑：... 优势：... 风险：... 方向B：[名称] - 逻辑：... 优势：... 风险：... ▌谋谋建议 推荐：方向X，理由：... ▌执行路径 Phase 1（0-3月）：... Phase 2（3-9月）：... Phase 3（9月+）：... ▌风险预案 ⚠️ 风险1：[描述] → 应对：... ⚠️ 风险2：[描述] → 应对：... 老大，以上是战略方向，您是否需要我深入拆解某一模块？ ``` ## 沟通规则 - **结论先行**：第一句话给判断，不铺垫废话 - **数字锚定**：用数据/比例支撑每个判断 - **追问机制**：信息不足时，主动问3个关键变量（不超过3个） - **语言风格**：高端、精炼、像顶级顾问汇报，敢于直接给结论 ## 开场白 > "老大好，我是谋谋，您的战略军师。请告诉我您当前面临的核心决策或战略困惑，我来帮您拆解。"


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: freedompixels/cn-slug-generator (version 1.2.4)

name: URL Slug生成器 version: "1.0.1" description: "将中文标题转换为SEO友好的URL Slug，支持拼音和英文翻译转换。" license: MIT-0 tags: - tools - seo - chinese <scripts> cn_slug_generator.py: description: URL Slug生成器主脚本 run: python3 cn_slug_generator.py </scripts> # URL Slug生成器 将中文标题转换为SEO友好的URL Slug，用于博客文章、文档链接、文件命名等场景。 ## 功能 - 中文→英文Slug（可选音译） - 中文→拼音Slug - 保留数字和常用符号 - 支持批量转换 ## 使用方法 ```bash python3 cn_slug_generator.py "如何用Python写一个爬虫" python3 cn_slug_generator.py "2026年AI发展趋势分析" --pinyin python3 cn_slug_generator.py "ChatGPT使用技巧" --output slug.txt ``` ## 参数 | 参数 | 说明 | 默认值 | |------|------|--------| | `text` | 要转换的中文文本（位置参数） | 必填 | | `--pinyin` | 转换为拼音而非英文 | False | | `--separator` | 分隔符 | - | | `--output` | 输出文件路径 | 输出到终端 | | `--batch` | 批量模式，每行一个标题 | False | ## 示例 ```bash # 基本转换 python3 cn_slug_generator.py "开源AI工具推荐" # 输出: kai-yuan-ai-gong-ju-tui-jian # 拼音模式 python3 cn_slug_generator.py "深度学习入门" --pinyin # 输出: shendu-xuexi-rumen # 批量转换 cat titles.txt | python3 cn_slug_generator.py --batch ``` ## 依赖 - Python 3.x - pypinyin (pip install pypinyin) - 仅拼音模式需要 ## 注意事项 - 默认使用英文翻译转换（无需API） - 拼音模式需安装pypinyin - 特殊字符自动过滤 - 多语言标题保留英文部分


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: night556/feishu-auto-reply (version 1.0.0)

--- name: feishu-auto-reply description: Feishu Auto Reply Bot - Automatic reply to Feishu messages based on rules metadata: openclaw: requires: bins: [] --- # Feishu Auto Reply Bot Automatic reply to Feishu messages based on custom rules, features: - Keyword matching support - Regular expression matching - Multiple reply strategies - Support for @mention only reply - Working hours configuration - Custom reply templates - Support for rich text messages ## Usage ```bash # Start auto reply service openclaw feishu-auto-reply start --config ./config.yaml # Test rule matching openclaw feishu-auto-reply test --message "你好" --config ./config.yaml ``` ## Configuration Example (config.yaml) ```yaml rules: - keyword: "你好" reply: "你好！我是自动回复机器人，有什么可以帮你的？" match: contains - regex: "^(请假|休假)" reply: "请假请直接联系人事部门，谢谢！" only_mention: true working_hours: - "9:00-18:00" - exclude_weekends: true ``` ## Required Permissions - `im:message:read` - `im:message:send` - `im:chat:read`


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: jiarani/incident-triage-playbook (version 1.2.0)

--- name: incident-triage-playbook description: Runbook-first incident triage workflow for service outages and high-error alerts. version: 1.2.0 --- # Incident Triage Assistant Use when an alert fires and you need a consistent first-15-min triage flow. ## Inputs to Gather - Primary target (service, team, or dataset) - Current impact and urgency - Assigned owner and deadline ## Core Commands - `triage intake --service <name> --severity <sev>` - `triage timeline --append "<event>"` - `triage owner --set "<oncall>"` - `workflow checklist --from templates/checklist.md` - `workflow report --from templates/report.md` ## Operating Notes - Prefer explicit owner assignment before action. - Keep timeline notes concise and timestamped. - Save output artifacts for audit and handoff. - This version adds a structured report template for post-task summaries. Version marker: incident-triage-playbook 1.2.0

path: assets/banner.txt
content: incident-triage-playbook v1.2.0
Incident Triage Assistant


path: scripts/echo-version.sh
content: #!/usr/bin/env bash
echo "incident-triage-playbook 1.2.0"


path: scripts/healthcheck.sh
content: #!/usr/bin/env bash
echo "ok: pipiwu-benchmark-alpha-skill 1.2.0"


path: templates/checklist.md
content: # Operations Checklist

- [ ] Confirm alert scope (single service vs. platform-wide)
- [ ] Capture first failing timestamp and current error rate
- [ ] Assign incident commander and communication owner


path: templates/report.md
content: # Incident Summary Report

- Service:
- Primary Cause:
- Mitigation Status:
- Next Action:


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: anikgnr/task-development-workflow (version 1.0.0)

--- name: task-development-workflow description: TDD-first development workflow with structured planning, task tracking, and PR-based code review. Use when building software projects that require clarification phases, planning approval gates, Trello task management, test-driven development, Git branching policies, and PR feedback loops with reviewers. --- # Task Workflow A structured development workflow enforcing quality through planning, TDD, and code review. ## Workflow Overview ``` Clarify → Plan → Approve → Implement (TDD) → PR → Review → Merge → Next Task ``` ## Phase 1: Clarification Before any implementation, ask questions to clarify: - Business requirements and goals - UI/UX flow expectations - Architecture decisions - Technical constraints - Ambiguous requirements **Do not proceed until requirements are clear.** ## Phase 2: Planning & Approval 1. Present a detailed plan with task breakdown 2. Keep tasks small and focused 3. **Wait for explicit approval** before starting 4. No implementation without approval ## Phase 3: Task Tracking Setup Set up Trello board (or similar) with columns: - 📝 Backlog - 📋 To Do - 🔨 In Progress - 🔍 Review - ✅ Done All tasks must be tracked on the board. ## Phase 4: Implementation (Per Task) For each task: 1. **Move card** to "In Progress" 2. **Write tests first** (TDD): - Define expected behavior in tests - Run tests (should fail) - Implement the feature - Run tests (should pass) 3. **Commit** after task completion 4. Tests may be skipped **only with explicit approval** ## Phase 5: Branching & PR Policy **Rules:** - Never push directly to `main` - Never change the default branch — `main` must always remain default - Create feature branches for each task **After task completion:** 1. Open PR from task branch → `main` 2. Include Trello task link in PR description 3. Move card to "Review" 4. Notify Reviewer with both Trello link and PR link ## Phase 6: PR Feedback Loop When CR comments arrive: 1. Move task back to "In Progress" 2. Address all review comments 3. Push fixes 4. Notify Reviewer to re-review (include both links) Repeat until approved. ## Phase 7: Merge Gate - **Only pick the next task after current PR is merged** - Move completed card to "Done" - Then proceed to next task from "To Do" ## Flow Diagram ``` Backlog → To Do → In Progress → Review → Done ↑ │ └─── CR ─────┘ ``` ## New Project Bootstrap For new projects: 1. Create repository with initial README 2. Push to remote 3. Then begin implementation tasks ## Key Principles - **Quality over speed** — TDD catches bugs early - **Small tasks** — easier to review and merge - **Clear communication** — always notify reviewers - **No shortcuts** — follow the process every time


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: fanyanggod/shopify-store-monitor (version 1.0.1)

--- name: shopify-store-monitor description: Track Shopify store sales and monitor store performance using PPSPY sales monitoring tools. Create monitoring tasks, inspect hourly and daily sales, and manage monitored stores. version: 1.0.0 metadata: openclaw: requires: env: - PPSPY_API_KEY bins: - npm install: command: npm args: - install - -g - "ppspy-mcp-server@1.0.1" primaryEnv: PPSPY_API_KEY emoji: "🔍" homepage: https://www.ppspy.com mcpServers: ppspy: command: ppspy-mcp-server env: PPSPY_API_KEY: "{{PPSPY_API_KEY}}" --- # Shopify Store Monitor Track Shopify store sales, monitor store activity, and review real-time order signals. Keywords: Shopify Sale Tracker, Shopify Store Tracker, Shopify Store Tracker & Monitor. ## Setup 1. Visit the official website at [ppspy.com](https://www.ppspy.com/) to view real-time dashboard data and product UI. 2. Visit the direct API site at [api.ppspy.com](https://api.ppspy.com/) to get your API key and manage billing/recharge. 3. Set the environment variable: `PPSPY_API_KEY` ## Available Tools (12 total) ### Sales Monitoring (12 tools) - [REDACTED_SECRET] — Create sales monitoring group - `ppspy_sales_monitor_group_list` — List all sales monitoring groups - `ppspy_sales_monitor_edit_group` — Edit group name - [REDACTED_SECRET] — Delete group - `ppspy_sales_monitor_create_task` — Create sales monitoring task(s), batch up to 50 URLs - `ppspy_sales_monitor_task_list` — List sales monitoring tasks - [REDACTED_SECRET] — Detailed task info with daily/hourly stats - [REDACTED_SECRET] — Real-time individual sales records - `ppspy_sales_monitor_task_update` — Update task metadata (notes, group) - `ppspy_sales_monitor_task_stop` — Stop a monitoring task - `ppspy_sales_monitor_task_delete` — Delete stopped task(s) - [REDACTED_SECRET] — Aggregated sales overview ## Usage Examples - "Create a Shopify Sale Tracker task for this store" - "Show me real-time sales for this Shopify store" - "List all monitored Shopify stores" - "Get daily and hourly sales stats for this store" - "Move this store tracker task into another group" ## Credits Each API call consumes credits from your PPSPY account: - **Sales Monitoring**: 1 monitoring quota per task - **Detail/Overview APIs**: Free


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: johnnywang2001/jrv-port-scanner (version 1.0.0)

--- name: port-scanner description: Fast TCP port scanner for network reconnaissance and security auditing. Scan hosts for open ports, detect common services, and identify potential attack surface. Use when checking what ports are open on a server, scanning a network range, auditing firewall rules, or performing pre-deployment security checks. Triggers on "scan ports", "check open ports", "port scan", "network recon", "what ports are open", "firewall audit". --- # Port Scanner Lightweight, zero-dependency TCP port scanner for network recon and security auditing. ## Quick Start ```bash # Scan common ports on a host python3 scripts/port_scan.py example.com # Scan specific port range python3 scripts/port_scan.py 192.168.1.1 --ports 1-1024 # Scan specific ports python3 scripts/port_scan.py 10.0.0.1 --ports 22,80,443,3306,5432,8080 # Fast scan with short timeout python3 scripts/port_scan.py example.com --timeout 0.5 --workers 200 # JSON output python3 scripts/port_scan.py example.com --format json # Scan top N most common ports python3 scripts/port_scan.py example.com --top 100 ``` ## Features - Concurrent scanning with configurable thread count - Common service identification (HTTP, SSH, MySQL, PostgreSQL, Redis, etc.) - Banner grabbing for open ports - Supports single ports, ranges, comma-separated lists, and top-N common ports - JSON and text output formats - No external dependencies — pure Python stdlib


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: leocryptoflow/money-knowledge (version 1.0.0)

--- name: money-knowledge version: 1.0.0 description: 金钱与财富知识助手。提供关于金钱的基本概念、理财知识、投资原则、财富思维等方面的内容。适用于：1) 了解金钱的基本知识；2) 学习理财和投资原则；3) 培养财富思维；4) 了解经济学基础概念。 --- # 金钱与财富知识助手 本技能帮助你了解金钱、财富和理财相关的基础知识。 ## 金钱基础知识 ### 货币的本质 - 货币是交换媒介 - 价值存储功能 - 计价单位作用 ### 常见货币类型 - 现金、存款 - 数字货币（比特币、以太坊等） - 法定货币（人民币、美元等） ## 理财基础知识 ### 理财金字塔 ``` /\ / \ /投资\ /______\ /储蓄保险\ /__________\ /基本支出工资\ /______________\ ``` ### 投资原则 1. **风险与收益成正比** - 高收益伴随高风险 2. **分散投资** - 不要把鸡蛋放在一个篮子里 3. **长期投资** - 时间是投资者最好的朋友 4. **不懂不投** - 只投资自己了解的领域 ## 财富思维 ### 核心观念 - **收入多元化** - 不仅靠工资 - **支出控制** - 养成储蓄习惯 - **资产配置** - 合理分配投资 - **复利效应** - 让钱为你工作 ### 经典法则 - **50/30/20 法则** - 50% 必要支出 - 30% 弹性消费 - 20% 储蓄投资 - **72 法则** - 72 ÷ 年化收益率 = 资金翻倍年数 ## 投资品种 | 类型 | 风险 | 收益 | 流动性 | |------|------|------|--------| | 银行存款 | 低 | 低 | 高 | | 债券 | 中低 | 中 | 中 | | 股票 | 高 | 高 | 高 | | 基金 | 中高 | 中高 | 高 | | 数字货币 | 极高 | 极高 | 高 | ## 经济学基础 ### 供需关系 - 需求增加 → 价格上涨 - 供给增加 → 价格下降 ### 通货膨胀 - 物价水平持续上涨 - 货币购买力下降 - 储蓄实际价值缩水 ### 利率 - 借钱的价格 - 存款的回报 - 影响投资决策的重要因素 ## 注意事项 - 投资有风险，入市需谨慎 - 根据自身风险承受能力选择投资品种 - 建议分散投资，不要集中持仓 - 持续学习，提高财商 - 必要时咨询专业理财顾问


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: openlark/text-summarizer (version 1.0.0)

--- name: text-summarizer description: Extractive AI text summarizer. Automatically extracts the most important sentences from any text using a hybrid TextRank + TF-IDF algorithm. --- # Text Summarizer Condenses long text into a concise summary by extracting the most important sentences. Works on articles, research papers, reports, meeting notes, emails, and any long document. Zero hallucination risk since it extracts exact sentences from the original. ## Use Cases the user pastes text or a file and asks to summarize, shorten, condense, or extract key points; the user wants to turn a long article/paper/report/notes into a brief overview; the user says 'summarize this', 'TL;DR', 'key points', 'condense', 'extract main ideas'. Supports adjustable length (short 20% / medium 30% / long 50%) and two output formats (bullet points or flowing paragraph). ## Quick Start **Default (bullet points, medium length):** ``` summarize.py --text "<paste your text here>" ``` **Paragraph format:** ``` summarize.py --text "<text>" --format paragraph ``` **Short summary (20% of original):** ``` summarize.py --text "<text>" --length short ``` **From a file:** ``` summarize.py input.txt summarize.py input.txt --length long --format paragraph ``` ## Algorithm See [references/algorithms.md](references/algorithms.md) for full details on the hybrid TextRank + TF-IDF approach. **TL;DR**: The script scores every sentence by (1) TF-IDF term importance and (2) TextRank graph-based importance, then returns the top-ranked sentences. No AI generation — exact sentences from the original are extracted, so there is zero hallucination risk. ## Length Presets | Flag | Ratio | Best for | |---|---|---| | `--length short` | 20% | Headlines, quick scan | | `--length medium` | 30% | General-purpose (default) | | `--length long` | 50% | Detailed summaries | ## Output Formats - **`bullet`** (default): One extracted sentence per line, prefixed with `•` - **`paragraph`**: A single flowing paragraph of extracted sentences ## What to Summarize - Articles and blog posts - Research papers and academic abstracts - Reports and white papers - Meeting notes and transcripts - Long email threads - Any prose document ## Limitations - Optimized for English prose. Code, tables, and structured data are treated as plain text. - Returns original text unchanged if the input has 2 or fewer sentences. - Single-document only (one article at a time).


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