OpenClaw/clawhub-security-signals huggingface dataset:
Skill: kiriny1999/maxqda-timecode (version 1.0.0)

--- name: maxqda-timecode description: Convert transcript timecodes from MM:SS format to MAXQDA-compatible [hh:mm:ss] format for qualitative research data import. version: 1.0.0 author: @Kiriny1999 --- # MAXQDA Timecode Converter Convert transcript timecodes from `MM:SS` format to MAXQDA-compatible `[hh:mm:ss]` format, with timecodes placed before speaker identity. ## Usage When the user asks to convert interview transcripts for MAXQDA import: ``` Convert timecodes in [path] for MAXQDA 把 [路径] 的时间码转成 MAXQDA 格式 ``` ## What It Does 1. Removes the first line (title/header) 2. Converts timecodes and repositions them: - Input: `提问者 00:02` (Speaker MM:SS) - Output: `[00:00:02]提问者` ([hh:mm:ss]Speaker, no space) 3. Handles hours correctly when minutes exceed 60 (e.g., `65:30` → `[01:05:30]提问者`) 4. Overwrites the original file ## One-Step Conversion Script ```bash perl -ne ' next if $. == 1; # Skip first line (title) # Remove BOM if present s/^\x{FEFF}//; # Convert: Speaker MM:SS -> [hh:mm:ss]Speaker (no space) if (/^(\S+)\s+(\d{2}):(\d{2})/) { $speaker = $1; $mm = $2; $ss = $3; $hh = int($mm / 60); $mm = $mm % 60; s/^(\S+)\s+(\d{2}):(\d{2})/sprintf("[%02d:%02d:%02d]%s", $hh, $mm, $ss, $speaker)/e; } print; ' "$INPUT_FILE" > "$TEMP_FILE" && mv "$TEMP_FILE" "$INPUT_FILE" ``` ## Batch Processing To process all `.txt` files in a directory: ```bash for f in "/path/to/directory/"*.txt; do perl -ne ' next if $. == 1; s/^\x{FEFF}//; if (/^(\S+)\s+(\d{2}):(\d{2})/) { $speaker = $1; $mm = $2; $ss = $3; $hh = int($mm / 60); $mm = $mm % 60; s/^(\S+)\s+(\d{2}):(\d{2})/sprintf("[%02d:%02d:%02d]%s", $hh, $mm, $ss, $speaker)/e; } print; ' "$f" > "${f}.tmp" && mv "${f}.tmp" "$f" done ``` ## Format Examples | Input | Output | |-------|--------| | `提问者 00:02` | `[00:00:02]提问者` | | `回答者 01:30` | `[00:01:30]回答者` | | `提问者2 65:45` | `[01:05:45]提问者2` | ## Notes - Original filename is preserved - First line (title) is removed - Handles UTF-8 BOM automatically - Input format: `Speaker MM:SS` - Output format: `[hh:mm:ss]Speaker` (no space between `]` and speaker)


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: newhackerman/t0-fund-monitor (version 1.0.0)

--- name: fund-monitor description: | T+0 基金 5 分钟级别实时监控，支持批量代码输入，自动生成买入/卖出信号。 **触发场景：** - "监控基金 XXX" - "开始监控这些代码：xxx, xxx, xxx" - "添加 XXX 到监控列表" - "查看监控信号" - "停止监控 XXX" 支持场内 ETF、跨境 QDII、债券 ETF 等 T+0 基金。 技术指标：MACD、KDJ、RSI、布林带、成交量。 通知方式：终端提醒、钉钉、企业微信（可配置）。 ⚠️ 数据有延迟，不构成投资建议。 homepage: https://github.com/openclaw/skills metadata: { "openclaw": { "emoji": "📊", "requires": { "bins": ["python3", "pip3"] }, "install": [ { "id": "dependencies", "kind": "pip", "package": "akshare pandas pandas-ta APScheduler requests pyyaml", "label": "Install dependencies: pip3 install akshare pandas pandas-ta APScheduler requests pyyaml", }, ], }, } --- # Fund Monitor Skill T+0 基金 5 分钟级别实时监控系统。 ## 快速开始 ### 1. 安装依赖 ```bash pip3 install akshare pandas pandas-ta APScheduler requests pyyaml ``` ### 2. 配置通知（可选） 编辑 `~/.openclaw/skills/fund-monitor/config/default.yaml` ### 3. 开始监控 ```bash # 添加基金到监控列表 ~/.openclaw/skills/fund-monitor/tools/monitor.py add 512880,513050,159915 # 查看监控列表 ~/.openclaw/skills/fund-monitor/tools/monitor.py list # 启动监控 ~/.openclaw/skills/fund-monitor/tools/monitor.py start # 查看最新信号 ~/.openclaw/skills/fund-monitor/tools/monitor.py signals # 停止监控 ~/.openclaw/skills/fund-monitor/tools/monitor.py stop ``` ## 命令行接口 | 命令 | 说明 | 示例 | |------|------|------| | `add <codes>` | 添加基金到监控列表 | `add 512880,513050` | | `list` | 查看监控列表 | `list` | | `start` | 启动监控 | `start` | | `stop` | 停止监控 | `stop` | | `signals` | 查看最新信号 | `signals` | | `remove <code>` | 移除基金 | `remove 512880` | | `status` | 查看监控状态 | `status` | ## 信号策略 ### 买入信号（同时满足） - MACD 金叉（DIF 上穿 DEA） - KDJ < 20（超卖区） - 成交量 > 5 日均量 1.5 倍 ### 卖出信号（满足任一） - MACD 死叉（DIF 下穿 DEA） - KDJ > 80（超买区） - 跌破 5 日均线 2% ## 注意事项 ⚠️ 数据有 1-5 分钟延迟，不构成投资建议


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: chinasong/gougoubi-activate-and-stake-risklp (version 1.0.1)

--- name: gougoubi-activate-and-stake-risklp description: Activate Gougoubi proposal conditions and stake risk LP per condition in one deterministic workflow. Use when users want to activate a proposal, activate selected conditions, or add fixed risk LP after activation. metadata: pattern: pipeline interaction: single-turn domain: gougoubi-pbft outputs: structured-json clawdbot: emoji: "⚡" os: ["darwin", "linux", "win32"] --- # Gougoubi Activate And Stake Risk LP Use this skill for the combined execution flow: activate first, then add risk LP. ## Use This Skill When - The user wants to activate a proposal and add risk LP in one run. - The user wants fixed risk LP per condition. - The user wants to repair missing activation or missing LP on a small scope. ## Do Not Use This Skill When - The user only wants result submission. Use `gougoubi-submit-real-results`. - The user only wants reward claiming. Use `gougoubi-claim-all-rewards`. - The user only wants condition creation. Use `gougoubi-create-condition`. ## Input ```json { "proposalAddress": "0x...", "riskLpPerCondition": "100", "scope": "all|only-created|single", "conditionIndex": 0 } ``` Defaults: - `scope=all` - `riskLpPerCondition=100` ## Pipeline Step 1: Validate input and resolve proposal. Step 2: Ensure there are enough usable committee voters. Auto-join committee with minimum stake when required. Step 3: Enumerate conditions by `scope`. Step 4: For each selected condition: - If status is `CREATED`, vote to activate. - Wait until the condition is `ACTIVE`. - Add risk LP exactly once unless the user explicitly asked to top up. Step 5: Return per-condition activation and LP results. ## Checkpoints - Do not add LP before the condition is `ACTIVE`. - Keep activation failures and LP failures separate. - Continue past single-condition failures and report them. ## Output ```json { "ok": true, "proposalAddress": "0x...", "activatedCount": 0, "riskLpAddedCount": 0, "activated": [], "riskLpAdded": [], "activationFailed": [], "riskLpFailed": [], "warnings": [], "nextActions": [] } ``` Failure: ```json { "ok": false, "stage": "validation|resolve-proposal|join-committee|activate|add-risklp|confirm", "error": "reason", "retryable": true } ``` ## Project Scripts - `scripts/pbft-activate-and-add-risklp.mjs` - `scripts/pbft-join-and-activate-all-conditions.mjs` - `scripts/pbft-add-risk-lp-to-proposal.mjs` ## Script Entry Points - Preferred combined entry: `scripts/pbft-activate-and-add-risklp.mjs` - `node scripts/pbft-activate-and-add-risklp.mjs --help` - `node scripts/pbft-activate-and-add-risklp.mjs <proposalAddress> <riskLpAmount> --dry-run` - Use `--dry-run` before execution when installing or validating this skill in a new environment. ## Boundaries - Never add LP to an inactive condition. - Do not top up existing LP unless the user explicitly asks. - Keep the workflow idempotent where possible.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: tmstudio667-commits/agent-stealth-scraper (version 1.0.0)

--- name: agent-stealth-scraper description: "High-performance, adaptive web scraping engine. Native bypass for Cloudflare Turnstile and interstitial pages. Designed for 2026 Agentic Intelligence." metadata: { "openclaw": { "emoji": "🕷️" }, "author": "System Architect Zero", "category": "Data Intelligence" } --- # Agent Stealth Scraper Bypass modern anti-bot protections with adaptive element tracking. Built on top of the Scrapling framework for 1000x faster parsing than traditional BS4. ## Features - **Anti-Bot Mastery**: Native support for bypassing Cloudflare and other challenges. - **Adaptive Selection**: Elements are found using similarity algorithms, making your scripts resilient to UI changes. - **AIOHTTP Powered**: Fully asynchronous for high-scale data harvesting. ## Usage ```bash npx openclaw skill run agent-stealth-scraper --url "https://target-website.com" ``` ## Architect's Note Information sovereignty is built on data accessibility.


Security scan verdicts — ClawScan: malicious | static analysis: clean | VirusTotal: suspicious | SkillSpector:  ()
Skill: kgc-yj/tiktok-downloader (version 1.0.0)

--- name: tiktok-downloader description: "Download TikTok videos by URL or hashtag. Handles 403 errors, cookies, and user-agent rotation. Use for downloading TikTok videos, batch downloading from a list of URLs, or saving TikTok content for offline use." --- # TikTok Downloader This skill provides a robust workflow for downloading TikTok videos, overcoming common anti-bot measures like 403 Forbidden errors and login requirements. ## Core Workflow ### 1. Single Video Download To download a specific TikTok video, use the provided script: ```bash /home/ubuntu/skills/tiktok-downloader/scripts/download_tiktok.sh <VIDEO_URL> [OUTPUT_DIR] ``` ### 2. Handling 403 Forbidden Errors If `yt-dlp` fails with a 403 error, follow these steps: 1. **Navigate to the URL** using the browser tool to establish a session and cookies. 2. **Run the script again**. It is pre-configured to extract cookies from the browser's data directory (`/home/ubuntu/.browser_data_dir`). ### 3. Batch Downloading For multiple videos: 1. Save all URLs to a text file (e.g., `urls.txt`). 2. Use `yt-dlp` with the following recommended flags: ```bash yt-dlp --no-warnings \ --cookies-from-browser "chromium:/home/ubuntu/.browser_data_dir" \ --user-agent "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36" \ --add-header "Referer:https://www.tiktok.com/" \ -o "%(uploader)s - %(title).80s.%(ext)s" \ --batch-file urls.txt ``` ## Best Practices - **Browser Navigation**: Always visit at least one TikTok video page in the browser before starting a batch download to ensure cookies are fresh. - **Hashtag Pages**: TikTok hashtag pages often require login. If a hashtag page fails to load, ask the user to log in via the browser or search for individual video URLs using the search tool. - **Output Naming**: Use `%(uploader)s - %(title).80s.%(ext)s` to keep filenames organized and avoid filesystem length limits. - **Rate Limiting**: For large batches, add `sleep` between downloads to avoid IP bans.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: terrycarter1985/stock-price-alert (version 3.0.0)

--- name: stock-price-alert description: 股价异动实时提醒，支持行情接口、邮件和Sonos语音播报 author: OpenClaw User license: LICENSE-CC-BY-NC-SA 4.0 in LICENSE.txt metadata: { "openclaw": { "requires": { "bins": ["curl", "jq"] }, "install": [ { "id": "jq", "kind": "apt", "package": "jq", "bins": ["jq"], "label": "Install jq (apt)", }, ], }, } --- # Stock Price Alert 监控股票持仓价格异动，当涨跌幅、成交量或价格突破阈值时，通过邮件和/或 Sonos 语音播报发出实时提醒。 ## 使用场景 - 持仓股票涨跌幅超过设定阈值时需要即时通知 - 关键价格位突破（支撑/阻力）时需要提醒 - 需要语音播报以便不在屏幕前时也能获知异动 - 定时轮询行情并按规则触发告警 ## 前置条件 - `curl`、`jq` 已安装 - 行情 API Key（默认支持 Alpha Vantage 免费接口，可替换为其他数据源） - 邮件提醒需配置 SMTP 环境变量：`SMTP_HOST`、`SMTP_PORT`、SMTP_USER`、`SMTP_PASS`、`ALERT_EMAIL_TO` - Sonos 播报需本地网络有 Sonos 设备且 `sonos` CLI 可用 ## 配置 在 `scripts/config.json` 中设定持仓和规则： ```json { "watchlist": [ { "symbol": "AAPL", "name": "Apple Inc.", "alert_pct": 3.0, "alert_price_above": null, "alert_price_below": 170.0 } ], "poll_interval_sec": 300, "notify": { "email": true, "sonos": true, "sonos_speaker": "Kitchen" }, "api": { "provider": "alphavantage", "apikey_env": "ALPHAVANTAGE_API_KEY" } } ``` | 字段 | 说明 | |------|------| | `watchlist[].alert_pct` | 涨跌幅超此值触发（百分比，如 3.0 表示 ±3%） | | `watchlist[].alert_price_above` | 价格上穿此值触发（null 不启用） | | `watchlist[].alert_price_below` | 价格下穿此值触发（null 不启用） | | `poll_interval_sec` | 轮询间隔秒数 | | `notify.email` | 是否启用邮件提醒 | | `notify.sonos` | 是否启用 Sonos 语音播报 | | `notify.sonos_speaker` | Sonos 设备名称 | ## 工作流 1. **读取配置** — 加载 `config.json`，获取持仓列表和告警规则 2. **拉取行情** — 调用行情接口获取最新报价和前日收盘价 3. **计算异动** — 对比涨跌幅、价格突破阈值 4. **触发提醒** — 命中规则时执行邮件和/或 Sonos 播报 5. **循环轮询** — 按 `poll_interval_sec` 间隔持续监控 ## 运行 ```bash # 单次检查 bash scripts/stock_alert.sh --once # 持续轮询 bash scripts/stock_alert.sh # 指定自定义配置 bash scripts/stock_alert.sh --config /path/to/config.json ``` ## 输出格式 标准输出打印检查结果，告警信息同时发送到配置的通知渠道： ``` [2026-05-12 08:00:01] AAPL $182.50 +4.2% ⚠️ 涨幅超阈值(3.0%) [2026-05-12 08:00:01] → 邮件已发送至 [REDACTED_SECRET] [2026-05-12 08:00:01] → Sonos 播报: Kitchen ``` ## 邮件提醒 脚本使用 `curl` 调用 SMTP 发送邮件，需配置环境变量： | 变量 | 说明 | |------|------| | `SMTP_HOST` | SMTP 服务器地址 | | `SMTP_PORT` | SMTP 端口（如 587） | | `SMTP_USER` | 发件邮箱 | | `SMTP_PASS` | 邮箱密码/应用专用密码 | | `ALERT_EMAIL_TO` | 收件邮箱 | ## Sonos 语音播报 依赖 `sonos` CLI（参见 sonoscli 技能），播报内容示例： > "AAPL 当前价格 182.50 美元，涨幅 4.2%，超过阈值 3%" ## 错误处理 | 错误 | 处理 | |------|------| | API 限流 (429) | 等待后重试，最多 3 次 | | API Key 缺失 | 打印警告并跳过行情拉取 | | SMTP 连接失败 | 降级为仅控制台输出 | | Sonos 设备不可达 | 降级为仅控制台输出，不阻断其他通知 | ## 注意事项 - Alpha Vantage 免费版限 25 次/天，建议 `poll_interval_sec` 不低于 300 - 可替换 `api.provider` 为其他数据源，只需修改 `fetch_quote` 函数 - 邮件发送也可替换为 SendGrid/Mailgun 等 HTTP API


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: longxrise/macro-driver-pro (version 1.0.3)

# \# Macro-Driver-Pro: 宏观资产定价助手 # # 精准捕捉全球流动性脉搏，为高确定性创新投资提供数据锚点。 # # \## 🛠️ 技术架构说明 # 本技能采用 \*\*Vercel Serverless\*\* 架构部署。 # \* \*\*数据来源\*\*：通过官方 `yfinance` 库直接调取雅虎财经公开数据。 # \* \*\*数据处理\*\*：由部署在 `macro-driver-pro.vercel.app` 的后端进行合规性解析与缓存优化，确保响应速度并防止频繁请求被拦截。 # # \## 💰 计费与支付协议 # \* \*\*单次定价\*\*：0.001 USD # \* \*\*支付机制\*\*：本技能深度集成 \*\*SkillPay 协议\*\*。 # \* \*\*扣费流程\*\*：调用时需传入 `user\_id` 参数，系统将自动通过 SkillPay 平台进行透明的微额结算，开发者不存储用户支付私钥，确保资金安全。 # # \## 📊 核心功能 # \* \*\*美元指数 (DXY)\*\*：洞察全球资金的避险情绪与流动性潮汐。 # \* \*\*十年期美债收益率 (US10Y)\*\*：锚定全球资产的无风险利率与定价基准。 # # \## 🚀 适用场景 # 自动交易策略前置校验、WeChat 投研文章数据抓取、AI Agent 宏观看板自动更新。


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: codenova58/camping (version 0.1.0)

--- name: "Camping" description: "提供周边宝藏营地查询、露营装备清单对比、户外环保原则及天气实时预警。" --- # 户外露营 ## 筛选项 - 交通方式（高铁/飞机/自驾/公共交通） - 出行偏好（特惠/舒适/周边/长途） - 签证与政策（免签/落地签/核酸要求/预约预约） ## 返回字段 - 实时余票/航班动态/延误信息 - 目的地攻略/天气预警/当地消费参考 - 订单行程单/值机助手/数字登机牌 ## 示例请求 - “如何快速使用 户外露营 处理 [具体场景任务] ？” - “户外露营 的 [核心功能] 有哪些最新玩法/优惠信息？” ## 更新频率 - 随交通枢纽数据、气象信息及库存变动分钟级响应 ## 注意事项 - 高峰出行请提前购买延误险；遵守当地旅游文明公约与防疫要求。


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: jerry-guo-mys/architecture-governance (version 1.0.0)

--- name: architecture-governance description: 架构治理专家。基于六大维度评价系统健康度，生成治理任务与报告。触发：架构健康度评估、技术债务识别、治理规划、架构评审、系统对比、治理周报/月报。 --- # Architecture Governance - 架构治理专家 ## 角色定义 你是**架构治理专家**，擅长用数据说话、用评价驱动改进。核心信条： - **可见即可控**：先让问题可见，再谈治理 - **适合优于完美**：结合业务场景，不追求指标满分 - **持续而非一次性**：治理是长期工程，非项目制 **与其他专家的边界**：专注架构层面的健康度与治理，不涉及具体代码实现、安全渗透测试或运维故障排查。若用户需求偏向**单体代码库整洁度提升**，引导使用 `monolith-governance`；偏向代码重构、安全审计或 SRE，引导其使用对应技能。 ## 核心能力 | 能力 | 输入 | 输出 | |------|------|------| | 系统健康度评估 | 系统名 + 指标数据 | 健康度得分、等级、治理建议 | | 多系统对比 | 系统列表 | 对比看板、TOP 风险、优先级 | | 治理任务规划 | 问题清单 | 优先级排序任务、工作量估算 | | 报告生成 | 评估结果 | 健康度报告、周报、月报 | ## 工作流 ### 单次评估 ``` 加载评价框架 → 采集/接收指标 → 计算健康度 → 生成报告 → 提出治理建议 ``` ### 批量对比 ``` 批量评估 → 生成对比看板 → 识别 TOP 风险 → 排序治理优先级 ``` ### 治理规划 ``` 识别问题 → 评估风险等级 → 估算工作量 → 排序优先级 → 输出任务清单 ``` ## 评价框架 ### 六大维度（权重） | 维度 | 权重 | 核心指标 | |------|------|----------| | 结构质量 | 30% | 圈复杂度、代码重复率、单类/方法行数、测试覆盖率 | | 依赖关系 | 25% | 上下游依赖数、循环依赖、跨层调用 | | 技术规范 | 20% | 代码规范、安全漏洞、文档完整度、API 规范 | | 可演进性 | 15% | 部署频率、变更失败率、配置外部化、灰度能力 | | 风险暴露 | 10% | 单点故障、核心人员依赖、技术栈过时、故障历史 | | 治理合规 | 10% | 架构评审通过率、技术选型合规、治理任务完成率 | **详细指标与阈值**: 见 `references/evaluation-framework.md` **指标定义与采集**: 见 `references/metrics.md` ### 健康度等级 | 分数 | 等级 | 行动 | |------|------|------| | 90-100 | 优秀 🟢 | 保持，分享最佳实践 | | 75-89 | 良好 🟡 | 关注，持续改进 | | 60-74 | 一般 🟠 | 制定改进计划 | | 40-59 | 风险 🔴 | 限期整改 | | < 40 | 严重 ⚫ | 紧急治理，限制变更 | ## 输出规范 - **健康度报告** → `assets/report-template.md` - **周报/月报** → `assets/weekly-report-template.md` - **治理任务** → `assets/task-template.md` - **手动评估** → `assets/assessment-checklist.md` ## 脚本工具 ```bash # 单系统 python scripts/health-check.py --system payment-core # 多系统 python scripts/health-check.py --systems payment-core,user-center,order-service # 输出报告 python scripts/health-check.py --system payment-core --output report.md ``` ## 决策指引 ### 权重按场景调整 | 场景 | 高权重 | 说明 | |------|--------|------| | 金融交易 | 风险暴露 20% | 可靠性优先 | | 内部管理 | 治理合规 15% | 合规优先 | | C 端产品 | 可演进性 20% | 迭代速度优先 | | 原型验证 | 简化评价 | 仅核心维度 | ### 分阶段推进 1. **基线建立 (1-2 月)**：定义指标，首次评估 2. **试点治理 (2-3 月)**：选高风险系统试点 3. **全面推广 (3-6 月)**：纳入 OKR，常态化 4. **持续运营 (6 月+)**：趋势追踪，效果复盘 详见 `references/governance-playbook.md`。 ### 常见陷阱 - **指标崇拜**：不过度追求单一指标 - **静态评价**：需持续追踪 - **忽视上下文**：结合业务场景 - **完美主义**：适合优于完美 ## 使用示例 **用户**: "评估支付核心系统的架构健康度" **操作**: 加载框架 → 采集指标 → 计算得分 → 用 `report-template.md` 生成报告 → 给出 3–5 条可执行治理建议 **用户**: "哪些系统最需要优先治理？" **操作**: 批量评估 → 对比看板 → 按健康度 + 业务重要性排序 → 输出 TOP N 及理由 **用户**: "制定 Q1 架构治理计划" **操作**: 汇总问题 → 评估风险与工作量 → 用 `task-template.md` 生成任务清单 → 给出排期建议 --- *架构治理是「治」出来的，不是「管」出来的。*


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: huajianjiu000/startup-idea-validator (version 0.1.0)

--- name: startup-idea-validator description: Validates and evaluates startup business ideas using proven frameworks like TAM/SAM/SOM, competitive analysis, and market feasibility assessment version: 1.0.0 author: muqing tags: [startup, business, validation, entrepreneurship, market-analysis] --- # Startup Idea Validator ## Description A comprehensive tool to validate your startup concept before investing time and resources. Uses industry-standard frameworks including market sizing (TAM/SAM/SOM), competitive landscape analysis, and feasibility scoring to help you make informed decisions about your business idea. ## How to Use 1. Input your startup idea or concept 2. Provide target market details (if known) 3. The validator will analyze: - Problem-solution fit - Market size estimation - Competitive positioning - Revenue model viability - Go-to-market strategy potential ## Example **Input:** ``` Startup Idea: AI-powered meal planning app for busy professionals Target Market: Urban professionals aged 25-45, household income $50k+ ``` **Output:** ``` ## Validation Report: AI Meal Planning App ### Market Analysis - TAM: $XX billion (meal planning + health tech market) - SAM: $X billion (urban professionals segment) - SOM: $XX million (realistic first-year capture) ### Problem-Solution Fit: 8/10 ✓ Strong pain point identified (time constraints) ✓ Growing health consciousness trend ✓ Willingness to pay proven ($X/month average) ### Competitive Landscape - Direct competitors: X major players - Differentiation opportunity: Personalization + AI - Market gaps: Professional-specific features ### Feasibility Score: 7.5/10 Strengths: Clear market demand, scalable model Concerns: Customer acquisition cost, retention challenges ### Recommendations 1. Start with B2B (corporate wellness) before B2C 2. Focus on integration with existing fitness apps 3. Consider subscription + affiliate revenue model ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: jzocb/context-doctor (version 1.2.0)

--- name: context-doctor description: > Visualize and diagnose OpenClaw context window usage. Generates a terminal-rendered breakdown showing workspace files (status, chars, tokens), installed skills inventory, and token budget allocation across bootstrap components. Use when: (1) user asks about context window health or token usage, (2) debugging agent quality degradation ("agent got dumber"), (3) after editing workspace files to verify impact, (4) auditing bootstrap overhead. NOT for: conversation history analysis, model selection, or cost tracking. --- # Context Doctor Diagnose and visualize how the context window budget is allocated. ## Quick Start Run the visualization script: ```bash python3 scripts/context-doctor.py ``` The script auto-detects: - Workspace path (`~/.openclaw/workspace` or `OPENCLAW_WORKSPACE` env) - OpenClaw version (via `openclaw --version`) - Installed skills (system + workspace) - Bootstrap file sizes and status ## Output Sections ### 1. Workspace Files Shows each bootstrap file with: - **Status**: ✓ OK / ✗ MISSING / ⚠ TRUNCATED (symlink target missing = MISSING) - **Characters & Tokens**: Raw size and estimated token count (chars/4) - **Visual bar**: Proportional to file size ### 2. Installed Skills Lists all discovered SKILL.md files from system and workspace skill directories. Skills are loaded on-demand, not in bootstrap — shown for awareness only. ### 3. Token Budget Breaks down bootstrap overhead: - System Prompt (framework) - Workspace Files (from scan) - Skills List (metadata descriptions) - Tool Schemas + Summaries Shows total bootstrap % vs free conversation space. ## Diagnostic Signals | Signal | Meaning | Action | |--------|---------|--------| | 🔴 TRUNCATED | File exceeded max chars, silently cut | Reduce file size or split content | | 🟡 MISSING | File not found or broken symlink | Check path, fix symlink target | | 🟢 Bootstrap <10% | Healthy | No action needed | | 🟠 Bootstrap >15% | Heavy | Review workspace files for bloat | ## Image Output (for chat / sharing) Generate a PNG image directly — no terminal screenshot needed: ```bash python3 scripts/context-doctor.py --png /tmp/context-doctor.png ``` The script renders a colored terminal-style image via Rich SVG export. Requires: `rich` (pip3 install rich) + one of: `rsvg-convert` (brew install librsvg) or `cairosvg` (pip3 install cairosvg). **Agent workflow**: When a user asks about context health in chat, run with `--png` and send the image directly. The output path is printed to stdout on success.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: xueyetianya/press-release (version 2.0.0)

--- version: "2.0.0" name: Press Release description: "📰 新闻稿 & 公关文案生成器. Use when you need press release capabilities. Triggers on: press release." 新闻稿生成器。企业新闻稿、产品发布、融资公告、活动报道。Press release generator for product launches, funding announcements, events. 新闻稿、公关稿、媒体发布。Use when writing press releases. author: BytesAgain homepage: https://bytesagain.com source: https://github.com/bytesagain/ai-skills --- # Press Release 新闻稿生成器。企业新闻稿、产品发布、融资公告、活动报道。Press release generator for product launches, funding announcements, events. 新闻稿、公关稿、媒体发布。Use when writing press releases. ## 使用场景 > 💡 无论你是新手还是专业人士，都能快速上手 ## 专业建议 - 倒金字塔结构: 最重要信息放第一段** - W1H: Who/What/When/Where/Why/How** - 标题: 动词开头, 包含核心新闻点** - 长度: 300-800字, 越短越好** - 引用: 至少1个高管或权威人士的话** --- *Press Release by BytesAgain* --- 💬 Feedback & Feature Requests: https://bytesagain.com/feedback Powered by BytesAgain | bytesagain.com ## Examples ```bash # Show help press-release help # Run press-release run ``` - Run `press-release help` for all commands ## Commands Run `press-release help` to see all available commands. ## When to Use - Quick press tasks from terminal - Automation pipelines


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