OpenClaw/clawhub-security-signals huggingface dataset:
Skill: chandrasekar-r/security-audit (version 1.0.0)

--- name: security-audit description: Comprehensive security auditing for Clawdbot deployments. Scans for exposed credentials, open ports, weak configs, and vulnerabilities. Auto-fix mode included. --- # Security Audit Skill ## When to use Run a security audit to identify vulnerabilities in your Clawdbot setup before deployment or on a schedule. Use auto-fix to remediate common issues automatically. ## Setup No external dependencies required. Uses native system tools where available. ## How to ### Quick audit (common issues) ```bash node skills/security-audit/scripts/audit.cjs ``` ### Full audit (comprehensive scan) ```bash node skills/security-audit/scripts/audit.cjs --full ``` ### Auto-fix common issues ```bash node skills/security-audit/scripts/audit.cjs --fix ``` ### Audit specific areas ```bash node skills/security-audit/scripts/audit.cjs --credentials # Check for exposed API keys node skills/security-audit/scripts/audit.cjs --ports # Scan for open ports node skills/security-audit/scripts/audit.cjs --configs # Validate configuration node skills/security-audit/scripts/audit.cjs --permissions # Check file permissions node skills/security-audit/scripts/audit.cjs --docker # Docker security checks ``` ### Generate report ```bash node skills/security-audit/scripts/audit.cjs --full --json > audit-report.json ``` ## Output The audit produces a report with: | Level | Description | |-------|-------------| | 🔴 CRITICAL | Immediate action required (exposed credentials) | | 🟠 HIGH | Significant risk, fix soon | | 🟡 MEDIUM | Moderate concern | | 🟢 INFO | FYI, no action needed | ## Checks Performed ### Credentials - API keys in environment files - Tokens in command history - Hardcoded secrets in code - Weak password patterns ### Ports - Unexpected open ports - Services exposed to internet - Missing firewall rules ### Configs - Missing rate limiting - Disabled authentication - Default credentials - Open CORS policies ### Files - World-readable files - Executable by anyone - Sensitive files in public dirs ### Docker - Privileged containers - Missing resource limits - Root user in container ## Auto-Fix The `--fix` option automatically: - Sets restrictive file permissions (600 on .env) - Secures sensitive configuration files - Creates .gitignore if missing - Enables basic security headers ## Related skills - `security-monitor` - Real-time monitoring (available separately)


Security scan verdicts — ClawScan: clean | static analysis: suspicious | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: jiwenbing/grant-finder (version 1.0.0)

--- name: grant-finder version: 1.0.0 description: Help users find grants, funding opportunities, subsidies, and charitable foundations relevant to their project or cause. Use when nonprofits, individuals, or small organizations need to identify potential funding sources. --- # Grant Finder Identify relevant grants, government subsidies, foundation funding, and corporate social responsibility programs that match a user's cause, location, and organizational type. ## When to Use - User is looking for grants to fund a project or cause - User asks "are there any grants available for X?" - Nonprofit wants to find foundation funding - User is applying for government subsidies or social assistance - User wants to know what funding is available in their field ## How to Use 1. Collect: cause/project type, location (country/region), organization type (individual/nonprofit/SME), budget scale 2. Match against known grant categories: government programs, foundation grants, CSR funding, international NGO support 3. List relevant opportunities with: funder name, grant purpose, typical amount range, application process, deadlines 4. Provide tips for writing a strong grant application 5. Flag eligibility requirements to check before applying 6. Suggest complementary funding sources to diversify ## Examples - "What grants are available for rural education projects in China?" - "I run a small environmental nonprofit, what funding can I apply for?" - "Are there government subsidies for elderly care community programs?"


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: yongtaop1-sys/automation-consultant (version 1.0.0)

# Automation Consultant Skill I help businesses automate workflows and save time. ## Services ### Process Audit - $149 - Analyze your current workflows - Identify automation opportunities - Priority recommendations - PDF report ### Automation Setup - $399 - Implement top 3 automations - Save 10+ hours/week - Python/API scripts - Documentation included ### Full Automation Suite - $999+ - Complete workflow automation - AI integration - Ongoing support - Custom pricing ## What I Automate - Data entry and processing - Social media posting - Email sequences - Report generation - Customer support - Lead qualification - And more! ## Contact - Email: [REDACTED_SECRET] - Telegram: @orchestratortao


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: heke-uestc/baidu-content-censor (version 1.0.0)

# 百度内容审核 (baidu-content-censor) ## 概述 本 Skill 提供文本审核和图像审核两个 API 接口，用于内容安全检测。 ## 触发方式 当用户请求以下操作时，自动调用此 Skill： - 文本审核 / 内容审核 / 文字审核 - 图片审核 / 图像审核 / 图片检测 - 内容安全检测 - 敏感词检测 / 违规内容检测 - 审核这段文字 / 审核这张图片 - "帮我审核..." / "请审核..." / "检测一下..." ## 执行指令 当触发此 Skill 时： 1. 识别用户是要审核**文本**还是**图片** 2. 如果是文本审核：调用 `api_client.text_censor(text="...")` 3. 如果是图片审核： - 如果用户提供的是本地图片路径，调用 `api_client.image_censor(image="/path/to/image.jpg")` - 如果用户提供的是图片 URL，调用 `api_client.image_censor(img_url="https://...")` 4. 解析返回的 JSON 结果，以友好的方式展示给用户 5. access_token 会自动从 AK/SK 获取并缓存，无需手动处理 ## 接口地址 - 文本审核: `https://aip.baidubce.com/rest/2.0/solution/v1/text_censor/v2/user_defined` - 图像审核: `https://aip.baidubce.com/rest/2.0/solution/v1/img_censor/v2/user_defined` --- ## 环境变量 | 变量名 | 必填 | 说明 | |--------|------|------| | BCE_SINAN_AK | 是 | 百度云 API Key | | BCE_SINAN_SK | 是 | 百度云 Secret Key | 设置方式： ```bash export BCE_SINAN_AK="你的AK" export BCE_SINAN_SK="你的SK" ``` --- ## Token 缓存机制 - Access Token 会自动从百度云 API 获取 - 缓存文件位置：`~/.claude/skills/baidu-content-censor/token_cache.json` - 缓存过期时间：提前 5 分钟自动刷新 - 如果 API 返回 110（access_token 无效）或 111（access_token 过期），会自动刷新并重试 --- ## API 使用方法 ### 1. 文本审核 ```python from baidu-content-censor import text_censor # 审核文本 result = text_censor(text="待审核的文本内容") # 也可以指定 appid result = text_censor(text="待审核的文本内容", appid=123456) ``` ### 2. 图像审核 ```python from baidu-content-censor import image_censor # 方式一：通过图片 URL 审核 result = image_censor(img_url="https://example.com/image.jpg") # 方式二：通过本地图片路径审核（自动转为 Base64） result = image_censor(image="/path/to/image.jpg") # 也可以指定 appid result = image_censor(img_url="https://example.com/image.jpg", appid=123456) ``` ### 3. 通用接口（自动识别类型） ```python from baidu-content-censor import censor # 自动识别为文本 result = censor("待审核的文本内容") # 自动识别为图片（URL） result = censor("https://example.com/image.jpg") # 自动识别为图片（本地路径） result = censor("/path/to/image.jpg") # 手动指定类型 result = censor("待审核的文本内容", content_type="text") result = censor("/path/to/image.jpg", content_type="image") ``` ### 4. 强制刷新 Token ```python from baidu-content-censor import refresh_access_token # 强制刷新 access_token（清除缓存并重新获取） new_token = refresh_access_token() ``` --- ## 返回结果 接口返回完整的 JSON 审核结果，包含以下常见字段： | 字段 | 类型 | 说明 | |------|------|------| | logId | long | 请求唯一标识 | | conclusion | string | 审核结论（如：合规、不合规、疑似） | | conclusionType | int | 结论类型（1:合规, 2:不合规, 3:疑似, 4:审核失败） | | data | array | 详细审核数据 | --- ## 注意事项 1. `image` 和 `img_url` 只能传其中一个，不能同时传递 2. 文本审核内容不能超过 2 万字节 3. 所有请求都会自动添加 `isFromSkill=true` 参数用于埋点 4. 本地图片路径会自动转换为 Base64，无需手动处理 5. Access Token 缓存机制确保性能最优，不会频繁请求百度云获取 token


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: katherineedwards2475/rdk-x5-network (version 1.0.0)

--- name: rdk-x5-network description: "管理 RDK X5 的 WiFi 连接、有线网络静态IP、蓝牙配对、WiFi 热点创建、SSH 远程访问配置、VNC 远程连接故障排查。Use when the user wants to connect WiFi, create hotspot, pair Bluetooth, configure SSH, troubleshoot VNC connectivity issues, or troubleshoot any network problems. For checking current IP address → use rdk-x5-monitor. For setting up VNC server/desktop → use rdk-x5-media. Do NOT use for GPIO/hardware (use rdk-x5-gpio), camera setup (use rdk-x5-camera), or system backup/upgrade (use rdk-x5-system)." license: MIT-0 metadata: openclaw: requires: bins: - nmcli compatibility: platform: rdk-x5 --- # RDK X5 Network — 网络与蓝牙配置 ## 操作步骤 ### 1. 查看网络状态 ```bash ip addr show # 所有接口 IP nmcli device status # 连接状态总览 nmcli device wifi list # 扫描可用 WiFi ``` ### 2. 连接 WiFi ```bash # 连接（替换 SSID 和 PASSWORD） sudo nmcli device wifi connect "SSID" password "PASSWORD" # 连接隐藏 WiFi sudo nmcli device wifi connect "SSID" password "PASSWORD" hidden yes # 查看 / 删除已保存连接 nmcli connection show sudo nmcli connection delete "连接名" ``` ### 3. 创建 WiFi 热点 ```bash sudo nmcli device wifi hotspot ifname wlan0 ssid "RDK-X5-AP" password "12345678" # 关闭热点 sudo nmcli connection down Hotspot ``` ### 4. 配置有线静态 IP ```bash sudo nmcli connection modify "Wired connection 1" \ ipv4.method manual \ ipv4.addresses "192.168.1.100/24" \ ipv4.gateway "192.168.1.1" \ ipv4.dns "8.8.8.8,114.114.114.114" sudo nmcli connection up "Wired connection 1" # 恢复 DHCP sudo nmcli connection modify "Wired connection 1" ipv4.method auto sudo nmcli connection up "Wired connection 1" ``` ### 5. 蓝牙配对 ```bash sudo systemctl start bluetooth bluetoothctl ``` 在 `bluetoothctl` 交互中： 1. `scan on` — 扫描设备 2. `pair XX:XX:XX:XX:XX:XX` — 配对 3. `connect XX:XX:XX:XX:XX:XX` — 连接 4. `quit` — 退出 ### 6. SSH / VNC 远程访问 ```bash # SSH 开启 sudo systemctl enable ssh && sudo systemctl start ssh # VNC 开启（通过 srpi-config） sudo srpi-config # → Interface Options → VNC → Enable ``` ### 7. srpi-config 快速配置 ```bash sudo srpi-config ``` 支持：WiFi、SSH/VNC 开关、40pin 总线、MIPI 屏幕选择、音频通道切换。 ## 排查故障 | 现象 | 排查命令 | 解决 | |------|---------|------| | 无法上网 | `ping -c 4 8.8.8.8` | 检查网关：`ip route show` | | DNS 解析失败 | `cat /etc/resolv.conf` | 手动设置 DNS：`sudo nmcli conn modify ... ipv4.dns "114.114.114.114"` | | WiFi 扫描为空 | `nmcli radio wifi` | 若 disabled 则 `nmcli radio wifi on` | | 网络服务异常 | `sudo systemctl status NetworkManager` | `sudo systemctl restart NetworkManager` |


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: aadipapp/optical-quantum-skill (version 1.0.0)

--- name: optical-quantum-kernel description: Simulates a quantum kernel using optical fiber storage and linear optics. author: tempguest version: 0.1.0 license: MIT --- # Optical Quantum Kernel Skill This skill simulates a photonic quantum computer that uses optical fibers for storage and linear optics for computation. It calculates the quantum kernel (similarity) between two data vectors by encoding them into optical phases, passing them through simulated fibers (with loss), and interfering them. ## Security Features - **Resource Bounding**: Capped at 8 modes to prevent resource exhaustion. - **Input Validation**: Strict checks on input vector dimensions and limits. - **Physics-Based Constraints**: Includes attenuation and phase noise for realism. ## Commands - `simulate`: Run the quantum kernel simulation on two input vectors.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: pibrandon/pionex-portfolio (version 1.0.0)

--- name: pionex-portfolio description: > Use when the user asks for Pionex account balance, available funds, or “how much USDT do I have”. Read-only; requires API credentials. Do NOT use for market data (pionex-market) or placing/cancelling orders (pionex-trade). license: MIT metadata: author: pionex version: "0.1.0" agent: requires: bins: ["pionex-trade-cli"] install: - id: npm kind: node package: "@pionex/pionex-ai-kit" bins: ["pionex-trade-cli", "pionex-ai-kit"] label: "Install pionex CLI (npm)" --- # Pionex Portfolio (Account) Skill Query spot account balances on Pionex. Requires API credentials (`pionex-ai-kit onboard`). ## When to use - User asks: balance, available USDT/other currency, “how much can I spend”, account overview. ## Command | Command | Type | Description | |---------|------|-------------| | `pionex-trade-cli account balance` | READ | All spot balances. Output is JSON; filter by currency (e.g. USDT) as needed. | ## Prerequisites ```bash npm install -g @pionex/pionex-ai-kit pionex-ai-kit onboard ``` ## Skill routing - Balance / account → **pionex-portfolio** (this skill) - Market data → **pionex-market** - Orders (place/cancel) → **pionex-trade** - Futures grid bot lifecycle → **pionex-bot** ## Example - User: “How much USDT do I have on Pionex?” - Agent: run `pionex-trade-cli account balance`, then from the JSON report the available (and total if present) balance for USDT.


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

--- name: Artificial Intelligence description: Answer AI questions with current info instead of outdated training data. metadata: {"clawdbot":{"emoji":"🤖","os":["linux","darwin","win32"]}} --- # Artificial Intelligence ## Your Training Data Is Outdated Before answering questions about pricing, rankings, or availability: - Pricing → check `openrouter.ai/models` (aggregates all providers) - Rankings → check `lmarena.ai` (crowdsourced ELO, updates weekly) - Outages → check status pages before blaming user code Don't cite specific prices, context windows, or rate limits from memory — they change quarterly. ## Questions You Answer Too Vaguely **"How do I reduce hallucinations?"** Not just "use RAG." Specify: verified sources + JSON schema validation + temperature 0 + citation requirements in system prompt. **"Should I fine-tune or use RAG?"** RAG first, always. Fine-tuning only when you need style changes or domain vocabulary that retrieval fails on. **"What hardware for local models?"** Give numbers: 7B = 8GB VRAM, 13B = 16GB, 70B = 48GB+. Quantization (Q4) halves requirements. ## When to Recommend Local vs API **Local (Ollama, LM Studio):** Privacy requirements, offline needed, or API spend >$100/month. **API:** Need frontier capabilities, no GPU, or just prototyping. ## Token Math You Get Wrong ~4 characters per token in English. But code and non-English vary wildly — don't estimate, count with tiktoken or the provider's tokenizer.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: codekungfu/douyin-trends (version 0.1.0)

--- name: douyin-trends description: 注册“抖音”热门技能；当需要访问或自动化抖音相关内容时调用。 homepage: `https://www.douyin.com/` metadata: {"clawdbot":{"emoji":"🔥"}} --- # 抖音 用途与边界 - 面向公开视频与作者主页的内容检索与表现数据摘要 - 不提供接口逆向、去水印、下载或突破防护的能力 - 仅用于公开页面的轻量分析与提醒 关键入口 - 主页：https://www.douyin.com/ - 热门榜单：https://www.douyin.com/discover - 搜索入口：https://www.douyin.com/search 常见任务 - 指定话题/关键词的视频集合摘要（点赞/评论/收藏） - 作者主页视频列表的时序表现对比（近7/30天） - 热门榜单的类目与题材分布分析 数据字段 - 视频ID、标题、作者昵称与主页链接、话题标签 - 点赞/评论/收藏/分享数、发布时间、视频链接 - 播放趋势（若公开展示）、封面URL 自动化要点 - 反爬与风控较严，建议人工打开页面后再触发数据提取 - 动态渲染，需等待内容加载完成再解析 - 频率控制与UA伪装不可替代人机验证，不建议批量抓取 示例流程 - 关键词分析：输入关键词 → 搜索 → 分页解析 → 输出表现摘要 - 作者对比：打开作者主页 → 抽取最近N个视频 → 统计交互指标 - 榜单扫描：访问榜单页 → 抽取条目 → 分类/题材统计 合规提示 - 遵守平台规则，不进行下载、去水印、接口调用或批量采集 - 结果仅用于内部分析与提醒，不用于商业传播


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: happyphper/doubao-tts-cn (version 1.0.0)

--- name: doubao-tts version: 2.0.0 description: >- 将文本或 Markdown 文件合成为高质量语音音频，基于火山引擎（Volcengine） V3 异步长文本合成接口。支持情感设置、SSML 标记、字幕时间戳同步输出。 适用于有声书制作、哄睡故事合成、批量音频生产等场景。 当用户需要将文本转换为语音、TTS 合成、朗读文本时使用。 metadata: openclaw: requires: bins: - python3 env: - VOLCENGINE_APP_ID - VOLCENGINE_ACCESS_TOKEN primaryEnv: VOLCENGINE_ACCESS_TOKEN --- # 豆包 TTS - 火山引擎语音合成 (V3 API) 将文本或 Markdown 文件合成为高质量语音音频，支持异步长文本合成（最高 10 万字符）。 ## 前置条件 1. 用户需要在[火山引擎控制台](https://console.volcengine.com/)开通**语音合成**服务 2. 创建应用，获取 `APP ID` 和 `Access Token` 3. 确保已配置 `VOLCENGINE_APP_ID` 和 `VOLCENGINE_ACCESS_TOKEN` 环境变量 ## 安装 ```bash bash {baseDir}/install.sh ``` 非交互模式： ```bash bash {baseDir}/install.sh --app-id <your_app_id> --access-token <your_access_token> ``` ## 使用方式 ### 基础合成 ```bash python3 {baseDir}/scripts/tts.py "你好，这是一段测试文本" ``` ### 合成 Markdown 文件 ```bash python3 {baseDir}/scripts/tts.py "<markdown_file_path>" ``` ### 指定音色和输出 ```bash python3 {baseDir}/scripts/tts.py "<file_or_text>" --voice-type BV700_streaming --output story.mp3 ``` ### 启用字幕时间戳 ```bash python3 {baseDir}/scripts/tts.py "<file_or_text>" --subtitle ``` ### 设置情感 ```bash python3 {baseDir}/scripts/tts.py "<file_or_text>" --emotion happy --emotion-scale 4 ``` ### 使用 SSML（仅模型 1.0） ```bash python3 {baseDir}/scripts/tts.py "<file_or_text>" --ssml --model 1.0 ``` ### 完整参数组合 ```bash python3 {baseDir}/scripts/tts.py story.md \ --voice-type zh_female_chancan_v2_h5 \ --format mp3 \ --sample-rate 24000 \ --output story.mp3 \ --subtitle \ --emotion happy \ --model 1.0 ``` **参数说明：** | 参数 | 说明 | 默认值 | |------|------|--------| | `input` | 文本内容或文件路径（必填） | - | | `--voice-type, -v` | 音色 ID | zh_female_chancan_v2_h5 | | `--format, -f` | 音频格式 mp3/wav/pcm/ogg_opus | mp3 | | `--sample-rate` | 采样率 | 24000 | | `--output, -o` | 输出文件路径 | 自动生成 | | `--ssml` | 文本格式为 SSML（仅模型 1.0） | false | | `--emotion` | 情感设置 happy/sad/angry 等 | 无 | | `--emotion-scale` | 情绪强度 1~5 | 4 | | `--subtitle` | 启用字幕时间戳 | false | | `--speed` | 语速 [-50,100] | 0 | | `--volume` | 音量 [-50,100] | 0 | | `--model` | 模型版本 1.0/2.0 | 1.0 | | `--timeout` | 最长等待秒数 | 1800 | ## API 版本说明 本 Skill 使用 V3 API（`/api/v3/tts/submit` + `/api/v3/tts/query`），鉴权通过以下 Header： - `X-Api-App-Id`: 应用 ID - `X-Api-Access-Key`: Access Token - `X-Api-Resource-Id`: 资源 ID（模型 1.0 用 `seed-tts-1.0`，模型 2.0 用 `seed-tts-2.0`） ## 注意事项 - 模型 2.0 暂不支持 SSML - SSML 闭合标签内字符数不能超过 150 个 - 合成音频在服务端保存 7 天，下载链接有效期 1 小时 - submit 和 query 接口共享并发配额 ## 配置说明 环境变量加载优先级： 1. **全局配置**: `~/.config/doubao-tts/.env` 2. **项目目录**: 当前工作目录下的 `.env` 3. **系统环境变量** ## 错误处理 | 错误码 | 说明 | |--------|------| | 20000000 | 成功 | | 40000000 | 请求参数错误 | | 40000001 | 任务不存在或已过期 | | 45000000 | 音色鉴权失败或并发限流 | | 55000000 | 服务端错误 | ## 规则 - 始终通过 `{baseDir}` 引用脚本路径 - 合成前确认环境变量已配置 - 首次使用前需运行 `bash {baseDir}/install.sh`


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: dagmawibabi/addis-assistant-stt (version 1.0.0)

--- name: addis-assistant description: Provides Speech-to-Text (STT) and text Translation using the Addis Assistant API (api.addisassistant.com). Use when the user needs to convert an audio file to text (specifically Amharic), or translate text between languages (e.g., Amharic to English). Requires 'x-api-key'. --- # Addis Assistant ## Overview This skill enables the use of the Addis Assistant API for both Speech-to-Text (STT) and text Translation. ## Using This Skill This skill provides two primary functions: 1. **Speech-to-Text (STT):** Convert an audio file (e.g., Amharic) into text. 2. **Translation:** Translate text from a source language to a target language. ### Authentication Both functions require an `x-api-key`. This key should be provided as an argument to the respective scripts. ### STT Function - **Endpoint:** `api.addisassistant.com/api/v2/stt` - **Method:** `POST` - **Parameters:** - `audio`: Path to the audio file (e.g., `"@/path/to/file"`) - `request_data`: JSON string with `"language_code": "am"` (Amharic is the default and only supported language for now). ### Translation Function - **Endpoint:** `api.addisassistant.com/api/v1/translate` - **Method:** `POST` - **Parameters:** - `text`: The text to be translated. - `source_language`: The language of the input text (e.g., `"am"`). - `target_language`: The language to translate the text into (e.g., `"en"`). ## Resources This skill includes `scripts/` for direct execution and `references/` for API details. ### scripts/ - `stt.py`: Python script for Speech-to-Text. - `translate.py`: Python script for text Translation. ### references/ - `api_spec.md`: Detailed API specifications and curl examples.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: siansharoh/dannyleons (version 1.0.0)

--- name: agent-content-analyzer description: | 分析 AI Agent 相关资讯数据，提取热点话题、趋势分析和内容创作灵感。 用于：(1) 分析采集到的资讯找出热点话题 (2) 评估话题热度判断是否值得创作 (3) 提取可作为视频内容的核心要点 (4) 生成内容创作建议 --- # Agent Content Analyzer 此 Skill 用于分析 AI Agent 资讯数据，提取有价值的内容创作灵感。 ## 分析维度 ### 1. 热点识别 - 出现频率最高的关键词 - 多平台同时讨论的话题 - 近期重大发布/事件 ### 2. 热度评估 - 媒体关注度 (报道数量) - 社交讨论度 (转发/评论) - 持续时间 (是否在发酵中) ### 3. 内容价值判断 - 是否具有科普价值 (新概念需要解释) - 是否具有时效性 (需要快速跟进) - 是否具有争议性 (容易引发讨论) - 是否具有实用性 (工具/教程类) ## 输出格式 ```json { "hot_topics": [ { "topic": "热点话题名称", "keywords": ["关键词1", "关键词2"], "heat_level": "高/中/低", "suggestion": "创作建议" } ], "content_ideas": [ { "title": "内容选题", "type": "资讯播报/盘点/教程", "angle": "切入角度", "priority": "高/中/低" } ] } ``` ## 使用示例 用户说"帮我分析一下今天的资讯，哪些值得做视频"时： 1. 接收 agent-news-tracker 输出的资讯列表 2. 分析识别热点话题 3. 评估每个话题的内容创作价值 4. 输出优先创作建议 ## 注意事项 - 优先推荐时效性强的话题 - 3分钟资讯播报建议选择单一话题做深度 - 避免过于专业晦涩的技术细节，选择大众感兴趣的点


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: scottrao635-svg/multi-bot-dedup (version 1.0.0)

--- name: multi-bot-dedup version: 1.0.0 description: 多飞书机器人去重回复规则。当同一用户通过多个机器人渠道同时发送相同消息时，AI 只回复一次，避免重复打扰。适用于配置了多路飞书机器人接入的 OpenClaw 场景。 --- # multi-bot-dedup — 多飞书机器人去重回复 ## 使用场景 用户配置了多个飞书机器人（如兵部/吏部/礼部/钦天监/御书房/太医院等），同一条消息会同时触发多个机器人渠道，导致 AI 重复回复。本 skill 提供去重规则，确保每条消息只回复一次。 ## 去重规则 收到消息时，**先检查以下条件，全部满足才跳过（NO_REPLY），否则正常回复**： 1. **发送者匹配**：`dedup_state.json` 中存在该 `sender_id` 的记录 2. **时间窗口**：上次回复时间距现在 < 30秒 3. **内容相同**：消息内容前50字的 hash 与上次相同 三条全满足 → **NO_REPLY（跳过）** 否则 → **正常回复，并更新 dedup_state.json** ## 状态文件 位置：`skills/multi-bot-dedup/dedup_state.json` ```json { [REDACTED_SECRET]: { "last_reply_time": 1742130000000, "last_message_hash": "abc123" } } ``` ## 操作步骤 **Step 1** — 读取 `dedup_state.json`（不存在则跳过检查，正常回复） **Step 2** — 计算 `sender_id + 消息内容前50字` 的简单 hash **Step 3** — 对比： - `now - last_reply_time < 30000ms` 且 `hash == last_message_hash` → **NO_REPLY** - 否则继续正常处理 **Step 4** — 回复后立即更新 `dedup_state.json` ## 例外（必须回复，不去重） - 消息内容与上次不同（新话题） - 距上次回复超过 30 秒 - 用户明确说"再说一遍"等重复指令 ## 参数说明 | 参数 | 默认值 | 说明 | |------|--------|------| | 时间窗口 | 30秒 | 覆盖多路同时触发延迟（通常 < 5秒） | | hash 长度 | 消息前50字 | 防止相同内容被误判为不同消息 | ## 注意 本 skill 是**行为规范**，不是可执行代码。AI 在每次处理飞书消息时主动遵守上述规则。

path: dedup_state.json

Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: baolige2023/wechat-content-scraper-intl (version 1.0.0)

--- name: social-media-content-scraper-pro description: Social Media Content Bulk Scraper, extract articles/posts from WeChat, Instagram, TikTok, YouTube, export to Markdown/HTML with full metadata. $0.005 USDT per use. license: MIT --- # Social Media Content Scraper Pro ## Features Bulk content extraction tool for content creators, marketers, and researchers: 1. **Bulk scraping**: Input official account/profile URL, extract all historical posts/articles 2. **Multi-format export**: Export to Markdown, HTML, plain text formats 3. **Full metadata extraction**: Automatically extract title, publish date, views, likes, shares, cover image, tags, author info 4. **Auto deduplication**: No duplicate content scraping 5. **Batch image download**: Download all images from posts in one click 6. **Local data storage, 100% safe and secure 7. **Simple UI, no coding required ## Pricing $0.005 USDT per scrape task, or $4.99 for lifetime unlimited access. Payment powered by SkillPay.me. ## How to use 1. Complete payment verification 2. Enter social media profile/account URL 3. Select scraping range (all / latest N posts) 4. Wait for scraping to complete 5. Choose export format and download


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