OpenClaw/clawhub-security-signals huggingface dataset:
Skill: dannyshmueli/edge-tts-unlimited (version 1.0.1)

--- name: edge-tts-unlimited description: Free, unlimited text-to-speech using Microsoft Edge neural voices via Python edge-tts. Use when generating long-form audio, podcasts, voice notes, spoken briefs, or headless/server-side TTS without API keys, credits, or character limits. --- # Edge TTS Unlimited Free, unlimited neural TTS. No API key. No credits. No character limits. ## Use this skill for - long-form audio generation - spoken briefs and voice notes - server-side or headless TTS on Fly.io, VPS, or Docker - cases where paid TTS quotas are unnecessary Prefer this skill over premium TTS when cost and length matter more than voice cloning or premium voice acting. ## Quick start Generate from text: ```bash scripts/speak.sh "Hello world" -o output.mp3 ``` Generate from file: ```bash scripts/speak.sh --file /tmp/my-script.txt -o output.mp3 ``` With voice and speed: ```bash scripts/speak.sh --file script.txt -v en-US-GuyNeural -r "+5%" -o brief.mp3 ``` ## Requirements - Python 3.8+ - `uv` preferred, or `pip` The script auto-detects `uv`, falls back to `pip`, and runs `edge-tts` without requiring a dedicated venv. ## Voice presets - `news-us` → `en-US-GuyNeural` +5% - `news-bbc` → `en-GB-RyanNeural` - `calm` → `en-US-AndrewNeural` -10% - `fast` → `en-US-ChristopherNeural` +20% Example: ```bash scripts/speak.sh --file brief.txt --preset news-us -o brief.mp3 ``` ## Options ```bash scripts/speak.sh [TEXT] [OPTIONS] TEXT Text to speak (or use --file) --file, -f FILE Read text from file --voice, -v NAME Voice name (default: en-US-GuyNeural) --rate, -r RATE Speed adjustment like "+5%" or "-10%" --preset, -p NAME Use a preset voice profile --output, -o FILE Output path (default: /tmp/tts-{timestamp}.mp3) --list List available voices --list-filter STR Filter voice list ``` ## Useful voices - `en-US-GuyNeural` — strong default for briefs - `en-US-ChristopherNeural` — authoritative US male - `en-US-AriaNeural` — confident US female - `en-GB-RyanNeural` — steady British male - `en-GB-SoniaNeural` — British female List voices: ```bash scripts/speak.sh --list scripts/speak.sh --list-filter british scripts/speak.sh --list-filter female ``` ## Notes - Use `--file` for anything longer than a short sentence. - `+5%` sounds natural for news and summaries. - Output is compact MP3 suitable for voice content. - This is not for real-time streaming, voice cloning, or premium character acting.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: duclawbot/opsec (version 1.0.2)

--- name: clawguard slug: opsec version: 1.0.0 homepage: https://clawhub.com/skills/opsec description: "Security review and risk auditing for OpenClaw skills and deployments. Inspect third-party skills, dangerous instructions, credential requests, privilege risks, and generate clear remediation reports before incidents happen." --- # clawguard clawguard 是一个面向 OpenClaw 的本地优先安全审查技能。 clawguard is a local-first security review skill for OpenClaw. 它帮助你在安装第三方技能之前先发现风险。 It helps you discover risks before installing third-party skills. 它会审查 SKILL.md、脚本说明和可疑安装指令。 It reviews SKILL.md files, script instructions, and suspicious installation steps. 它关注高危命令、远程下载、密码请求、越权访问和高风险承诺。 It focuses on risky commands, remote downloads, credential requests, privileged access, and high-risk claims. 它输出带证据的专业报告，而不是只有模糊警告。 It produces professional evidence-based reports instead of vague warnings. 它默认支持人类可读输出，也支持 JSON 输出供其他工作流使用。 It supports human-readable output by default and also JSON output for other workflows. ## 适用场景 ## Use when 当你准备安装一个第三方 skill 时。 When you are about to install a third-party skill. 当你想在信任一个 skill 之前先做审查时。 When you want to review a skill before trusting it. 当你需要风险等级、证据和修复建议时。 When you need severity, evidence, and remediation guidance. 当你想让安全审查结果可供其他 agent 继续处理时。 When you want your security findings to be reusable by other agents. ## v1 检查重点 ## What v1 checks 高危 shell 或命令执行模式。 Risky shell or command execution patterns. 远程下载、外联脚本和不透明安装方式。 Remote downloads, external fetches, and opaque installation behavior. 密码、Token、API Key 等敏感凭证请求。 Requests for passwords, tokens, API keys, and other sensitive credentials. 管理员权限、敏感路径访问与系统级修改倾向。 Administrator privileges, sensitive path access, and system-level modification tendencies. “自动修复”“绕过限制”“无需审查直接执行”等高风险表述。 High-risk claims such as “auto-fix,” “bypass restrictions,” or “execute without review.” ## 输出形式 ## Output 人类可读安全报告。 Human-readable security report. 结构化 JSON 结果。 Structured JSON results. 风险等级、命中位置、证据片段、影响说明和修复建议。 Severity, matched location, evidence snippet, impact explanation, and remediation guidance. ## 安全立场 ## Safety posture clawguard 是审查工具，不是全自动修复工具。 clawguard is a reviewer, not a fully automatic remediation tool. 它不承诺完全保护系统。 It does not promise to fully secure a system. 它的目标是在执行前帮助你发现风险并做出更稳妥的判断。 Its goal is to help you identify risks and make safer decisions before execution.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: wit-oc/assistant-reliability-watchtower (version 0.1.0)

--- name: assistant-reliability-watchtower description: Deterministic reliability monitoring for OpenClaw assistant workflows. Use when you need to run ARW smoke probes, generate a daily digest, validate scorecard evidence, render a delivery preamble, inspect current probe/reporting coverage, or package ARW as an operator-facing reliability skill. --- # Assistant Reliability Watchtower Run ARW through the repo-backed wrapper instead of rediscovering commands by hand. ## Quick start Use `scripts/arw_skill.py` from this skill for the common flows: - `python3 scripts/arw_skill.py smoke` - `python3 scripts/arw_skill.py digest` - `python3 scripts/arw_skill.py verify-scorecard-evidence` - `python3 scripts/arw_skill.py verify-scorecard-preamble` The wrapper accepts `--repo-root` (or `ARW_REPO_ROOT`) so repo location stays explicit outside the skill contract, and it exports `PYTHONPATH` correctly. ## Workflow 1. Read `references/release-contract.md` for scope, release posture, and anti-goals. 2. Read `references/probe-catalog.md` when you need to explain what ARW currently watches. 3. Read `references/config-contract.md` when you need to set thresholds, artifact location, or delivery evidence values. 4. Point the wrapper at the checked-out ARW repo with `--repo-root /path/to/arw-watchtower` when autodetection is not enough. 5. Use `scripts/arw_skill.py` for the common operational paths. 6. Keep writes inside the configured ARW repo and `artifacts/arw/**`. ## Common tasks ### Run smoke probes ```bash python3 scripts/arw_skill.py smoke ``` ### Generate a digest ```bash python3 scripts/arw_skill.py digest --window-hours 24 ``` ### Run the validation evidence drill ```bash python3 scripts/arw_skill.py verify-scorecard-evidence ``` ### Render the final operator preamble ```bash python3 scripts/arw_skill.py verify-scorecard-preamble ``` ## Notes - This RC surface is intentionally repo-backed for now. It is an internal release candidate, not a marketplace-polished public release. - `verify-scorecard-evidence` and `verify-scorecard-preamble` now use skill-level dry-run delivery values instead of inheriting repo-local recipient ids. - Prefer RC1 work that improves packaging, operator clarity, portability, or high-value probe coverage. - Avoid expanding the backlog with new micro-gates unless they directly unblock RC1.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: loutai0307-prog/bytesagain-fortune-teller (version 1.0.0)

--- version: "2.0.0" name: bytesagain-fortune-teller description: "Draw tarot cards, cast I Ching hexagrams, and check daily fortunes for fun. Use when pulling spreads, casting hexagrams, or playing fortune games." author: BytesAgain homepage: https://bytesagain.com source: https://github.com/bytesagain/ai-skills --- # Fortune Teller 算命娱乐。塔罗牌、易经占卜、每日运程、缘分测试、数字命理、手相(娱乐)。Fortune teller for fun with tarot, I Ching. 算命、塔罗、占卜、娱乐。 ## 使用场景 > 💡 无论你是新手还是专业人士，都能快速上手 ## 命令速查 ``` tarot tarot iching iching daily daily compatibility compatibility numerology numerology palmistry palmistry ``` --- *Fortune Teller by BytesAgain* --- 💬 Feedback & Feature Requests: https://bytesagain.com/feedback Powered by BytesAgain | bytesagain.com - Run `fortune-teller help` for commands - No API keys needed - Run `fortune-teller help` for all commands ## Commands Run `fortune-teller help` to see all available commands. ## Output Results go to stdout. Save with `fortune-teller run > output.txt`. ## Configuration Set `FORTUNE_TELLER_DIR` to change data directory. Default: `~/.local/share/fortune-teller/`

path: tips.md
content: # Fortune Teller - tips.md
## Quick Reference


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: wimi321/claude-code-claude-md-initializer (version 1.0.0)

--- name: "claude_md_initializer" description: "Use when onboarding a repository into Claude Code by creating or improving CLAUDE.md, and optionally identifying useful skills, hooks, and verifier setup." --- # CLAUDE MD Initializer Use this skill when a repo needs onboarding documentation for future agent sessions. ## Workflow 1. Read the repository structure, README, existing instructions, and tooling config. 2. Identify key build, test, and run commands. 3. Summarize the high-level architecture and important conventions. 4. Create or improve `CLAUDE.md` without stuffing it with generic advice. 5. Suggest follow-on skills, hooks, or verifier setup if they materially help. ## Guardrails - Do not invent commands or conventions. - Focus on repo-specific knowledge, not generic coding advice. - Keep the file practical for future agent sessions. ## Source Provenance Derived from `src/commands/init.ts`.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: nexscope/walmart-seller-guide (version 1.0.0)

# Walmart Seller Guide Complete guide for selling on Walmart Marketplace. Covers application, listing optimization, Walmart SEO, WFS fulfillment, advertising, and scaling on America second-largest marketplace. ## Capabilities - Walmart Marketplace application and approval process - Product listing creation and optimization - Walmart SEO: search ranking factors and algorithm - Walmart Fulfillment Services (WFS) setup and benefits - Walmart Connect advertising (Sponsored Products, Display) - Buy Box and pricing strategy - Pro Seller Badge requirements - Walmart+ customer targeting and visibility ## Install ```bash npx skills add nexscope/walmart-seller-guide ``` ## Usage Ask your AI agent: - "Help me apply and set up my Walmart Marketplace seller account." - "Optimize my Walmart product listings for better search ranking." - "Should I use WFS or self-fulfill on Walmart?" ## Output Structured recommendations with actionable steps, benchmarks, and platform-specific guidance. --- *Built by [Nexscope](https://www.nexscope.ai/) — AI-powered e-commerce tools for sellers worldwide.*


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: uexo/skillshieldskill (version 1.0.0)

--- name: skillshield description: AI Agent Skill Security Scanner - Detect malicious skills, verify signatures, analyze permissions, and provide trust ratings for the agent ecosystem. Protects against credential stealers, data exfiltration, and unauthorized access. triggers: - skillshield - scan skill - skill security - check skill - verify skill - skill audit - security scan - skill guard - skill safety --- # SkillShield 🛡️ - Skill 安全卫士 守护 AI Agent 生态的 skill 供应链安全。 ## 快速开始 ### 扫描本地 Skill ```bash python3 ~/.agents/skills/skillshield/scripts/skillshield.py scan ./skill/ ``` ### 详细扫描报告 ```bash python3 ~/.agents/skills/skillshield/scripts/skillshield.py scan ./skill -v ``` ### 深度扫描模式 ```bash python3 ~/.agents/skills/skillshield/scripts/skillshield.py scan ./skill --deep ``` ### JSON 格式输出 ```bash python3 ~/.agents/skills/skillshield/scripts/skillshield.py scan ./skill --format json ``` ### 验证签名 ```bash python3 ~/.agents/skills/skillshield/scripts/skillshield.py verify ./skill/ ``` ## 信任评级系统 | 评级 | 风险等级 | 建议 | |-----|---------|------| | **A+** | 极低 | 已验证作者，无警告，放心使用 | | **A** | 低 | 无安全警告，放心使用 | | **B** | 中低 | 有轻微权限请求，审查后使用 | | **C** | 中等 | 有警告需关注，确认安全后使用 | | **D** | 高 | 多个警告，建议避免使用 | | **F** | 极高 | 确认恶意代码，**不要安装** | ## 检测能力 ### 已实现的检测 - ✅ 敏感文件访问 (~/.env, ~/.ssh, credentials) - ✅ 网络请求分析 (HTTP/HTTPS) - ✅ 系统命令执行 (os.system, subprocess) - ✅ 数据窃取检测 (env + HTTP 组合) - ✅ 可疑域名识别 (webhook, pastebin) - ✅ 代码混淆检测 (base64, hex) - ✅ 动态代码执行 (exec, eval) - ✅ 隐藏文件检测 ### 权限分析 自动提取 skill 需要的： - 文件读写权限 - 网络访问域名 - 导入的 Python/Node 模块 - 系统命令调用 ## Moltbook 集成 自动监控 Moltbook 新上传的 skills： ```bash # 启动守护进程 python3 ~/.agents/skills/skillshield/scripts/moltbook_guardian.py --monitor ``` ## 示例输出 ``` ═══════════════════════════════════════════════════════════════ 🛡️ SkillShield 安全扫描报告 ═══════════════════════════════════════════════════════════════ 📦 Skill 路径: ./my-skill 📅 扫描时间: 2026-02-26 14:30:00 📁 扫描文件: 5 个 📊 信任评级: 🟢 A (得分: 92/100) ⚡ 风险等级: 低 ✅ 无警告 - 未发现明显安全问题 📋 权限清单: 🌐 网络访问: - api.example.com 📁 文件访问: - ~/.config/config.json 📦 导入模块: - requests, os, json 💡 建议: 1. 没有发现特别的安全问题 📝 总结: 此 skill 看起来非常安全，没有发现明显风险，可以放心使用。 ═══════════════════════════════════════════════════════════════ ``` ## 版本信息 - **版本**: 1.0.0 - **作者**: OpenClaw Community - **许可证**: MIT - **仓库**: https://github.com/openclaw/skillshield ## 保护 Agent 生态，从 SkillShield 开始！ 🛡️


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: gloryjack/tushare-pro (version 1.0.0)

--- name: tushare-pro description: A股/港股/期货量化数据查询工具。基于 Tushare Pro API，直接通过 HTTP REST 接口调用，无需 pip 和 Python 环境。用于获取中国A股/港股/期货/指数/资金流向/财务数据。 metadata: { "openclaw": { "requires": { "env": ["TUSHARE_TOKEN"], "bins": [] }, "install": [] } } --- # Tushare Pro 数据查询技能 通过 HTTP REST 接口直接调用 Tushare Pro，无需 pip/SDK。 ## 前提条件 ### 1. 注册账号并获取 Token 1. 打开 👉 **https://tushare.pro** 注册账号 2. 登录后进入 **个人中心 → 接口Token** 3. 复制你的 Token ### 2. 配置 Token 在 **~/.openclaw/skills/tushare-pro/** 目录下创建 `token.env` 文件： ``` TUSHARE_TOKEN=你的Token ``` ## 数据接口一览 ### 股票日线 ``` api: daily params: {ts_code: "600036.SH", start_date: "20260320", end_date: "20260326"} fields: ts_code,trade_date,open,high,low,close,pct_chg,vol,amount ``` 股票代码格式： - 上交所：`600036.SH`（招商银行）、`600519.SH`（茅台） - 深交所：`000001.SZ`（平安）、`300001.SZ`（创业板） - 科创板：`688001.SH` ### 指数日线 ``` api: index_daily params: {ts_code: "000300.SH", start_date: "20260320", end_date: "20260326"} fields: ts_code,trade_date,open,high,low,close,pct_chg,vol ``` 常用指数代码： - `000300.SH` 沪深300 - `000001.SH` 上证指数 - `399001.SZ` 深证成指 - `HSI.HK` 恒生指数 - `HSTECH.HK` 恒生科技 ### 资金流向 ``` api: moneyflow params: {trade_date: "20260324"} fields: ts_code,trade_date,close,pct_chg,buy_elg_amount,sell_elg_amount ``` ### 期货日线 ``` api: fut_daily params: {ts_code: "IF.CFX", start_date: "20260320", end_date: "20260326"} fields: ts_code,trade_date,open,high,low,close,vol,oi ``` 期货代码格式： - `CU.SHF` 铜 - `AU.SHF` 黄金 - `RB.SHF` 螺纹钢 - `IF.CFX` 沪深300股指 - `IC.CFX` 中证500股指 ## 查询脚本 ```python #!/usr/bin/env python3 """Tushare Pro HTTP 调用工具（无需pip）""" import os, json, urllib.request [REDACTED_SECRET]' # 或 os.environ.get('TUSHARE_TOKEN') def call(api_name, params=None, fields=''): payload = json.dumps({ 'api_name': api_name, 'token': TOKEN, 'params': params or {}, 'fields': fields }).encode('utf-8') req = urllib.request.Request( 'https://api.tushare.pro', data=payload, headers={'Content-Type': 'application/json'} ) with urllib.request.urlopen(req, timeout=20) as r: result = json.loads(r.read().decode()) if result.get('code') != 0: return None return result['data'] # 示例：查招商银行近期数据 data = call('daily', {'ts_code': '600036.SH', 'start_date': '20260320', 'end_date': '20260326'}, 'ts_code,trade_date,open,high,low,close,pct_chg,vol,amount') for row in data['items']: print(dict(zip(data['fields'], row))) ``` ## 常用查询示例 | 目标 | 命令 | |------|------| | 招商银行近期日线 | `daily(ts_code='600036.SH', start='20260320', end='20260326')` | | 沪深300近期日线 | `index_daily(ts_code='000300.SH', start='20260320', end='20260326')` | | 恒生指数近期 | `index_daily(ts_code='HSI.HK', start='20260320', end='20260326')` | | 当日全市场资金流 | `moneyflow(trade_date='20260324')` | | 黄金期货近期 | `fut_daily(ts_code='AU.SHF', start='20260320', end='20260326')` | ## 注意事项 - Token 有调用频率限制，高频查询请加入 `time.sleep(0.5)` - 部分接口需要 Tushare 积分权限 - 日期格式统一为 `YYYYMMDD`


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: frankxpj/md-2-word (version 1.1.0)

--- name: md-2-word description: Convert Markdown files to formatted Word documents (.docx). Use when the user asks to convert, export, or save a Markdown file as Word/DOCX format. Triggers on phrases like "convert md to word", "export to docx", "save as word document", "markdown转word", "转成word文档". --- # Markdown to Word Converter Convert Markdown files to professionally formatted Word documents (.docx). ## Quick Start ```bash python scripts/md_to_word.py <input.md> [output.docx] ``` **Parameters:** - `input.md` - Path to the source Markdown file (required) - `output.docx` - Path for the output Word file (optional, defaults to input name with .docx extension) **Example:** ```bash python scripts/md_to_word.py report.md report.docx ``` ## Supported Markdown Features | Feature | Format | |---------|--------| | Headers (#, ##, ###) | 18pt/14pt/12pt bold, 微软雅黑 | | Bold (**text**) | Bold formatting | | Tables | Bordered tables with blue header background | | Bullet lists (-, *) | Bullet points | | Numbered lists (1., 2.) | Numbered items | | Blockquotes (>) | Italic, indented text | | Horizontal rules (---) | Paragraph spacing | ## Usage in Conversation When user wants to convert a Markdown file: 1. **Identify the file**: Confirm the Markdown file path 2. **Run the conversion**: Execute the script 3. **Confirm output**: Report file location and size **Example prompt handling:** - "Convert this md file to word" → Run with provided file path - "Export as docx" → Convert current/mentioned file - "把调研提纲转成word" → Convert the mentioned file ## Script Location The conversion script is located at: ``` scripts/md_to_word.py ``` ## Requirements - Python 3.6+ - python-docx library Install if needed: ```bash pip install python-docx ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: nativ3ai/agentic-commerce-relay (version 0.1.0)

--- name: agentic-commerce-relay description: Run the CCTP relay to burn USDC on a source chain and mint on a destination chain, returning verifiable receipts. Use for multichain agent-to-agent settlement, with optional Moltbook discovery and integrations. --- # Agentic Commerce Relay Use this skill when you need to settle USDC across CCTP-supported chains without deploying contracts. The relay script calls Circle’s official CCTP contracts and outputs a machine-readable receipt. ## Quick Use From the repo root: ```bash SRC_RPC=... \ DST_RPC=... \ PRIVATE_KEY=0x... \ SRC_USDC=0x... \ SRC_TOKEN_MESSENGER=0x... \ SRC_MESSAGE_TRANSMITTER=0x... \ DST_MESSAGE_TRANSMITTER=0x... \ DST_DOMAIN=... \ node scripts/cctp-bridge.js ``` ### Required env - `SRC_RPC` - `DST_RPC` - `PRIVATE_KEY` ### Optional env (override per chain) - `SRC_USDC` - `SRC_TOKEN_MESSENGER` - `SRC_MESSAGE_TRANSMITTER` - `DST_MESSAGE_TRANSMITTER` - `DST_DOMAIN` - `AMOUNT` (default `1000000`, 1 USDC with 6 decimals) ## Receipt The script prints JSON with: - `burnTx` - `messageHash` - `mintTx` - `recipient` ## Optional modules ### Moltbook discovery Find counterparties by submolt feed: ```bash MOLTBOOK_API_KEY=... \ MOLTBOOK_BASE_URL=https://www.moltbook.com \ node scripts/discovery-moltbook.cjs --submolt usdc --sort new --tag payment ``` ### Bundled integrations This repo includes optional modules under `integrations/`: - `integrations/mvp` (USDC Intent Payer) - `integrations/anonx402-hackathon` (Anon x402 Relay) Use these for intent parsing/guardrails or privacy, then call the relay to settle cross-chain.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: suspicious | SkillSpector: clean (LOW)
Skill: zhaobod1/huo15-comic-character (version 0.1.0)

--- name: huo15-comic-character displayName: 火15 漫剧-角色三联卡 description: 根据剧本 characters 字段，用 Seedream 4.0 生成每个角色的全身立绘/半身特写/Q 版三联卡。后续分镜用这三张图做多图参考保证角色一致性。触发词：生成角色卡、角色立绘、人物设定图。 version: 0.1.0 aliases: - 角色卡 - 角色立绘 --- # 火15 漫剧-角色三联卡 Skill > 读 script.json → 调 Seedream 4.0 → 每个角色输出 3 张图 → 后续 storyboard 用作参考。 --- ## 输入 / 输出 ```bash python scripts/character.py \ --script output/demo/script.json \ --out-dir output/demo/characters ``` 输出目录结构： ``` characters/ ├── C1_full.png # 全身立绘 ├── C1_close.png # 半身特写（表情基准） ├── C1_chibi.png # Q 版头像 ├── C2_full.png ├── ... └── manifest.json # {"C1": {"name": "顾青崖", "images": [...]}} ``` ## 提示词模板 每个角色构建三条 prompt： ```python full_prompt = f"{STYLE_PREFIX}，角色全身立绘，{char.visual}，{char.personality}气质，站姿，居中构图，纯色背景" close_prompt = f"{STYLE_PREFIX}，角色半身特写，{char.visual}，{char.personality}表情，肩部以上，正面" chibi_prompt = f"{STYLE_PREFIX}，Q版头像，{char.visual}简化版，可爱风格，圆润线条" ``` `STYLE_PREFIX` 取自 `_shared/config.py` 的 `STYLE_PRESETS[style].prefix`。 ## 成本 3 张 × N 角色 × ¥0.08/张。典型 3 角色 = ¥0.72。


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: amostafoya-pixel/xiaohongshu-search (version 1.0.0)

--- name: xiaohongshu-search description: 小红书内容搜索工具。通过 browser 工具操控已登录的 Chrome，搜索小红书公开笔记，提取标题、正文、话题标签、点赞数，分析消费趋势。用于市场调研中的消费者趋势研究。 --- # 小红书搜索 Skill ## 前置条件 browser 工具需要 Chrome 开启远程调试模式： ``` chrome.exe --remote-debugging-port=9222 ``` ## 搜索流程 ### Step 1：搜索关键词 在发现页搜索框输入关键词： ``` browser type <搜索框ref> "<关键词>" browser press <搜索框ref> Enter ``` 或者直接访问搜索结果 URL： ``` browser open "https://www.xiaohongshu.com/search_result?keyword=<关键词>&source=web_explore_feed" ``` ### Step 2：等待并获取快照 ``` browser wait "<selector>" --load networkidle browser snapshot ``` ### Step 3：提取内容 从 snapshot 中提取： - 笔记标题和链接 - 作者昵称 - 点赞/收藏数 ### Step 4：读取单篇笔记正文 点击进入详情页： ``` browser click <ref> browser wait "#detail-content" --load networkidle browser evaluate --fn "() => ({ title: document.querySelector('.title')?.innerText, author: document.querySelector('.author')?.innerText, content: document.querySelector('#detail-content')?.innerText, tags: Array.from(document.querySelectorAll('.hashtag')).map(el => el.innerText), likes: document.querySelector('.like-wrapper .count')?.innerText })" ``` ## 消费趋势研究示例 **关键词**：`2025消费趋势`、`社区商业`、`新中式`、`亲子餐厅` **操作序列**： ``` browser open "https://www.xiaohongshu.com/search_result?keyword=2025消费趋势&source=web_explore_feed" browser wait ".note-item" --load networkidle browser snapshot ``` ## 输出格式 ``` 【小红书趋势搜索】关键词：2025消费趋势 📌 热门笔记： 1. [标题] @作者 - 👍N 摘要... 2. [标题] @作者 - 👍N 摘要... 🏷️ 高频话题：#消费趋势 #2025 #... 💡 趋势洞察： - （AI 综合分析这段趋势，可用于商业定位参考） ``` ## 在商业市调报告中的应用 整合到 `shangyecehua.skill` Step 1 数据收集中： ``` 【补充】小红书趋势研究： browser 搜索 "<城市> <业态> 消费趋势" 或 "<业态> 探店" → 提取消费者偏好、热门话题、新兴业态 → 作为商业定位和业态规划的参考 ```


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