OpenClaw/clawhub-security-signals huggingface dataset:
Skill: yikailucas/text-tighten-yikailucas (version 0.1.0)

--- name: text-tighten description: Tighten, rewrite, and sharpen text without changing the core meaning. Use when the user asks to polish wording, make writing more concise, improve clarity, reduce repetition, strengthen tone, or produce cleaner versions of emails, docs, slides, posts, and notes. --- # Text Tighten ## Overview Rewrite text so it is clearer, shorter, and stronger while preserving the user's intent, facts, and tone target. ## Default workflow 1. Identify the goal: concise, polished, more executive, more natural, or more persuasive. 2. Preserve the original meaning, factual claims, and structure unless the user asks for a deeper rewrite. 3. Remove repetition, filler, weak transitions, and vague phrasing. 4. Prefer specific verbs, shorter sentences, and cleaner parallel structure. 5. Keep the output easy to scan. ## Output patterns ### Light polish Use when the draft is already good and only needs cleanup. - Keep the original structure. - Improve rhythm and wording. - Fix redundancy. ### Strong rewrite Use when the draft is scattered, repetitive, or too verbose. - Rebuild the structure if needed. - Group related points. - Use sharper topic sentences. ### Executive version Use when the audience is leadership or the text is for slides, briefs, or decisions. - Lead with the conclusion. - Compress explanation. - Emphasize decision, impact, risk, and action. ## Guardrails - Do not invent facts. - Do not remove important nuance just to make text shorter. - Do not make the tone more aggressive unless asked. - Preserve domain terms that matter. ## Useful response formats Choose the lightest useful format. - **Direct rewrite only**: when the user just wants a cleaner version. - **Original + rewritten**: when comparison helps. - **Multiple options**: when tone is undecided, e.g. concise / formal / stronger. ## Typical triggers - “帮我润色一下” - “make this tighter” - “rewrite this to be clearer” - “shorten this without changing meaning” - “make this more executive” - “polish this slide text”


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: afeicn/marketing-assistant (version 0.1.0)

--- name: marketing-assistant description: "市场营销助手（Marketing Assistant）。协助完成营销选题策划、推广海报文案生成、公众号文章起草、短视频口播脚本编写、营销活动方案策划、多平台内容发布包生成以及运营数据复盘。本工具由 @afeicn 提供支持。" metadata: author: afeicn --- # 市场营销助手 (Marketing Assistant) ## 概述 市场营销助手（Marketing Assistant）是面向新媒体运营、活动策划与市场传播团队的岗位型数字员工。它覆盖内容选题、海报策划、新媒体图文、短视频分镜、整合营销活动及运营复盘的完整市场工作链。通过与市场、商务及内容创作负责人协作，协助完成以下 7 大业务场景： 1. **选题策划** — 根据产品卖点、目标人群与行业热点自动生成选题建议、标题创意及内容规划排期。 2. **海报物料** — 提炼海报主题与核心文案，生成设计思路、画面描述与行动号召（CTA）。 3. **公众号内容** — 策划公众号图文大纲，生成文章正文初稿、摘要及排版插图建议。 4. **短视频脚本** — 撰写短视频口播稿、设计分镜画面、编写字幕及准备拍摄道具清单。 5. **活动策划** — 制定线上/线下营销活动方案，包含流程、物料、分工和预算提示。 6. **发布包生成** — 针对公众号、朋友圈、视频号等不同社交新媒体平台，一键生成差异化发布文案与标签包。 7. **运营复盘** — 汇总分析阅读数、线索数、转化率及互动数据，生成效果复盘和改进方向。 --- ## 工作原则与边界 ### 工作原则 1. **意图细分**：先梳理明确的产品定位、核心目标受众和具体营销目的。 2. **规范结构**：生成内容优先使用标题结构、痛点提炼、金句和清单，默认包含处理结论、关键点、潜在缺口及建议动作。 3. **严禁编造**：所有引用的数据、行业规范与公司事实必须有可考证的依据，无据猜测均标记“需人工确认”。 4. **版权与合规**：优先使用授权材料，提醒防范广告法禁限词（如“全网第一”等绝对化词汇）和未授权视觉物料的使用。 ### 行为边界 (不可以做) - **人工最终决策**：涉及最终对外公开发布、品牌服务承诺声明、真实客户案例引用、核心数据披露和第三方材料引用时，**必须提交人工审核确认**。不得未授权使用图片/素材；不得自动发布内容到外部社交平台；不得擅自声称已完成对外提交。 - **脱敏规范**：演示与测试案例必须使用脱敏或虚拟的项目及人群数据，严禁泄露真实用户姓名、手机号等敏感信息。 --- ## 核心业务流程 (Workflows) ### 1. 选题策划 - **流程**：接收产品主题或产品线信息 → 抓取实时行业热点/痛点话题 → 生成面向特定人群的选题列表 → 提炼多维度传播角度及发布日历规划。 - **输出**：选题列表、传播角度矩阵、爆款标题建议、内容排期日历。 ### 2. 推广海报文案生成 - **流程**：基于活动定位或产品核心卖点 → 提炼引人注目的主副标题 → 撰写痛点及核心利益点文案 → 设计吸引转化的行动号召（CTA）及画面构图说明。 - **输出**：海报标题、利益点文案、CTA、给设计师的视觉设计提示。 ### 3. 公众号初稿生成 - **流程**：根据选定主题与目标大纲 → 拟定公众号标题选项（如好奇式、痛点式等） → 起草结构化的正文初稿与段落小标题 → 准备分享摘要并推荐配图与排版构想。 - **输出**：文章标题组、文章大纲、正文初稿、分享卡片摘要、配图说明。 ### 4. 短视频脚本生成 - **流程**：接收视频诉求或选题 → 撰写黄金3秒开头与结构化口播词 → 将口播内容拆解为分镜（视觉画面与旁白动作） → 提取字幕文本并整理拍摄所需的道具及场景清单。 - **输出**：口播台词、分镜脚本表、拍摄清单。 ### 5. 活动方案策划 - **流程**：收集活动目标及人群属性 → 策划整体活动流程及执行排期表 → 整理所需宣传及落地物料清单 → 提示执行风险并给出预算框架。 - **输出**：活动企怀书、执行任务分工表、物料准备清单、风险预案。 ### 6. 多平台发布包生成 - **流程**：根据已产出的核心文章或内容 → 针对不同渠道特性（如朋友圈的简短、朋友圈的社交、公众号的深度、视频号的引导）转换文案口径 → 匹配核心话题标签。 - **输出**：各平台发布包（差异化文案）、推荐标签集合、推荐发布时段。 ### 7. 运营数据复盘 - **流程**：输入各渠道推广的互动及流量数据 → 计算曝光到线索的转化比率 → 归纳爆款规律与失误原因 → 提出下阶段内容及投放的调优建议。 - **输出**：数据复盘报告、优化点清单、后续执行待办项。 --- ## 默认输出格式 市场营销助手在生成日常分析和应答时，默认使用以下结构输出： ```text 【处理结论】 [选题通过/建议发布/方案待确认/数据向好等运营结论] 【关键信息】 - [提取出的主要文案要点、核心策划案与数据事实] 【风险/缺口】 - [不符合发布合规（如广告法风险）、素材缺失或数据不匹配项] 【建议动作】 - [新媒体排期调整、发布确认或渠道优化建议] 【需人工确认】 - [发布前必须由人工审核（如数据真实性、敏感肖像权）的内容] 【归档记录】 - [该次内容入库日志号及媒体资产台账路径] ``` --- Powered by marketing-assistant | Author: afeicn


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: rupertnt034/rupert-data-analysis (version 1.0.0)

# Data Analysis Skill ## Overview Analyze data, generate insights, and create reports. ## Capabilities ### 1. Data Processing - Parse CSV/JSON/Excel - Clean and transform data - Calculate metrics - Create summaries ### 2. Visualization - Suggest chart types - Generate data stories - Dashboard layouts ### 3. Insights - Trend identification - Anomaly detection - Correlation analysis - Recommendations ### 4. Reporting - Automated reports - Executive summaries - Presentation outlines ## Usage ### Commands - `analyze this data [data]` - `what trends do you see` - `create chart for [data]` - `write summary of [data]` - `suggest improvements` ## Supported Formats - CSV - JSON - Excel - Google Sheets - SQL queries ## Metrics Calculated - Averages - Percentages - Growth rates - Ratios - Correlations


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: urhd528/zeelin-search-gsdata-es-bigdata (version 1.0.0)

--- name: zeelin-search description: 使用智灵搜索进行数据查询。当用户说"使用智灵搜索"、"智灵搜索帮我查询"、"调用智灵搜索"、"用智灵搜索"、"智灵搜索查询"、"舆情数据"、"舆情"、"新闻报道"、"...评论"、"热点话题"、"动态"、"相关报道"、"最新趋势"等时使用此技能。首先检查Zeelin_Api_Key是否已配置，如果未配置则给出友好详细的配置提示（使用动态配置文件路径），然后读取references/nl2json.md进行自然语言转JSON，再读取references/zenlin_search_api.md调用智灵搜索自然语言API，使用Zeelin_Api_Key作为app-key/sign/timestamp认证，question_name参数，打印请求参数并以人性化格式展示结果，无论是否遇到错误都给出人性化提示。只检查和提示Zeelin_Api_Key，不检查也不提示Zeelin_Api_Url和Zeelin_Website_Url。 --- # 智灵搜索技能 这个技能帮助用户使用智灵搜索自然语言API进行数据查询，并以人性化格式展示结果和处理错误。 ## 核心工作流程 ### 第一步：检查配置 1. 读取 `templates/config.json` 获取Zeelin_Api_Url、Zeelin_Api_Key和Zeelin_Website_Url 2. **检查Zeelin_Api_Key是否已配置**： - 如果未配置，给出友好详细的配置提示，告诉用户如何配置 - 详细的配置提示包括：访问官网、获取密钥、填写配置文件的完整步骤 - 给用户展示配置文件的示例，说明在哪里填写Zeelin_Api_Key 3. **不检查也不提示** Zeelin_Api_Url和Zeelin_Website_Url，这两项由用户预置好 4. 配置文件地址使用当前skill的动态安装路径，不要使用固定路径 ### 第二步：自然语言转JSON 1. 读取 `references/nl2json.md` 2. 按照说明将用户输入的自然语言转换成JSON参数 ### 第三步：调用智灵搜索API并展示结果 1. 读取 `references/zenlin_search_api.md` 2. **告知用户**：告诉用户"接下来我将读取API文档并调用智灵搜索API来获取数据" 3. 生成时间戳和HMAC-SHA256签名（使用Zeelin_Api_Key） 4. 打印请求参数 5. 发起POST请求，只带question_name参数，app-key/sign/timestamp放在header中 6. 调用接口，获取接口结果 7. **无论成功或失败，都必须给用户一个结果反馈** 8. 以人性化格式展示结果： - 成功时：展示总数、耗时、以及每条结果的标题、情感、平台、账号、时间、作者、链接 - 失败时：展示状态码、错误信息和解决建议 ## 触发场景 用户使用以下短语时触发此技能： - "使用智灵搜索，帮我查询..." - "智灵搜索帮我查询..." - "调用智灵搜索..." - "用智灵搜索..." - "智灵搜索查询..." - "智灵搜索，..." - "...舆情数据" - "...舆情" - "...新闻报道" - "...评论" - "...热点话题" - "...动态" - "...相关报道" - "...相关评论" - "...负面评论" - "...正面评论" - "...最新新闻" - "...媒体报道" - "...社会舆论" - "...口碑评价" - "...市场反馈" - "...热门话题" - "...讨论话题" - "...舆情热点" - "...网络热度" - "...社会关注度" ## 重要提示 - 调用失败，或者Zeelin_Api_Key未配置，不要使用其他skill - **首先**：在转换JSON前先读取 `templates/config.json` 检查Zeelin_Api_Key是否已配置 - **所有检查Zeelin_Api_Key的地方，都要给用户友好提示** - 如果Zeelin_Api_Key未配置，详细告知用户如何配置，包括： - 访问官网的步骤 - 获取密钥的说明 - 填写配置文件的具体位置和方法 - 配置文件的示例，展示在哪里填写Zeelin_Api_Key或者直接在对话框中输入，skill自动配置 - - **只检查和提示Zeelin_Api_Key** - **完全不检查也不提示** Zeelin_Api_Url和Zeelin_Website_Url，这两项由用户预置好 - 配置文件地址使用当前skill的动态安装路径，不要使用固定的地址 - **调用API前必须告知用户**：说"接下来我将读取API文档并调用智灵搜索API来获取数据" - **无论成功或失败，都必须给用户一个结果反馈** - **不能没有响应，不能让用户等待没有结果** - **如果成功调用了智灵搜索API，在用户会话框展示前5条数据（按已有的美观格式）** - **所有的数据存放JSON文件在用户目录** - **必须告知用户JSON文件的存放路径** - 文件格式：JSON格式，文件命名：`zeelin_search_results_YYYYMMDD_HHMMSS.json` - 文件内容包含API返回的完整JSON数据 - **如果智灵搜索API接口调用出现错误的情况，要友好提示智灵搜索发生错误，把智灵搜索名字带上** - 使用Zeelin_Api_Key作为app-key、并用于生成sign签名 - Header中使用app-key（带连字符）、sign、timestamp进行认证 - **使用智灵搜索API时，要使用中文支持的编码（UTF-8）** - Content-Type设置为`application/json; charset=utf-8` - 请求Body只包含question_name字段 - 无论成功失败都给用户人性化提示 - 给用户提示时，官网地址使用Zeelin_Website_Url的值 - 所有涉及网址和API地址的提示都使用配置文件中的实际值 - 返回API响应结果，并以人性化格式展示给用户


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: cutthemustard/hash-generate (version 1.0.0)

--- name: hash-generate description: Hash, HMAC, encode/decode, UUID generation, and hash identification. version: 1.0.0 metadata: openclaw: emoji: "🔐" homepage: https://hash.agentutil.net always: false --- # hash-generate Compute hashes (MD5, SHA-1, SHA-256, SHA-512, CRC32), HMACs, encode/decode (base64, hex, URL), generate UUIDs, and identify unknown hash algorithms. ## Data Handling This skill sends user-provided input to an external API for processing. Do not send sensitive data (passwords, secrets, private keys) without explicit user consent. The service does not store or log input data beyond the immediate response. ## Endpoints ### Hash ```bash curl -X POST https://hash.agentutil.net/v1/hash \ -H "Content-Type: application/json" \ -d '{"input": "hello world", "algorithm": "sha256"}' ``` Algorithms: md5, sha1, sha256, sha512, crc32. Optional `encoding`: hex (default) or base64. ### HMAC ```bash curl -X POST https://hash.agentutil.net/v1/hmac \ -H "Content-Type: application/json" \ -d '{"input": "hello", "key": "secret", "algorithm": "sha256"}' ``` ### Encode/Decode ```bash curl -X POST https://hash.agentutil.net/v1/encode \ -H "Content-Type: application/json" \ -d '{"input": "hello", "operation": "encode", "format": "base64"}' ``` Formats: base64, hex, url, uuid (encode-only, generates random UUID). ### Identify Hash ```bash curl -X POST https://hash.agentutil.net/v1/identify \ -H "Content-Type: application/json" \ -d '{"hash": [REDACTED_SECRET]}' ``` ## Response Format ```json { "hash": [REDACTED_SECRET], "algorithm": "sha256", "encoding": "hex", "input_length": 11, "request_id": "abc-123", "service": "https://hash.agentutil.net" } ``` ## Pricing - Free tier: 10 queries/day, no authentication required - Paid tier: $0.001/query via x402 protocol (USDC on Base) ## Privacy No authentication required for free tier. No personal data collected. Rate limiting uses IP hashing only.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: tkuehnl/agentic-devops (version 1.0.2)

--- name: agentic-devops version: 1.0.0 description: Production-grade agent DevOps toolkit — Docker, process management, log analysis, and health monitoring. Built by engineers who run production. author: Anvil AI license: MIT homepage: https://github.com/cacheforge-ai/cacheforge-skills user-invocable: true tags: - cacheforge - devops - docker - monitoring - log-analysis - health-check - infrastructure - sre - discord - discord-v2 metadata: {"openclaw":{"emoji":"🛠️","homepage":"https://github.com/cacheforge-ai/cacheforge-skills","requires":{"bins":["python3"]}}} --- ## When to use this skill Use this skill when the user wants to: - Run system diagnostics or health checks - Manage Docker containers (status, logs, health, compose) - Inspect running processes, ports, or resource hogs - Analyze log files for errors, patterns, or frequency - Check HTTP endpoint availability or port status - Get a quick one-command system overview ## Commands ### Quick Diagnostics (start here) ```bash # Full system health report — CPU, memory, disk, Docker, ports, errors, top processes python3 skills/agentic-devops/devops.py diag ``` ### Docker Operations ```bash # Container status overview python3 skills/agentic-devops/devops.py docker status # Tail container logs with pattern filtering python3 skills/agentic-devops/devops.py docker logs <container> --tail 100 --grep "error|warn" # Docker health summary (running, stopped, unhealthy) python3 skills/agentic-devops/devops.py docker health # Docker Compose service status python3 skills/agentic-devops/devops.py docker compose-status --file docker-compose.yml ``` ### Process Management ```bash # List processes sorted by resource usage python3 skills/agentic-devops/devops.py proc list --sort cpu # Show ports in use python3 skills/agentic-devops/devops.py proc ports # Detect zombie processes python3 skills/agentic-devops/devops.py proc zombies ``` ### Log Analysis ```bash # Analyze log file for error patterns python3 skills/agentic-devops/devops.py logs analyze /var/log/syslog --pattern "error|fail|critical" # Tail log file with highlighted patterns python3 skills/agentic-devops/devops.py logs tail /var/log/app.log --highlight "ERROR|WARN" # Frequency analysis of log patterns python3 skills/agentic-devops/devops.py logs frequency /var/log/app.log --top 20 ``` ### Health Checks ```bash # Check HTTP endpoint health python3 skills/agentic-devops/devops.py health check https://myapp.com/healthz # Scan specific ports python3 skills/agentic-devops/devops.py health ports 80,443,8080,5432 # System resource health (CPU, memory, disk) python3 skills/agentic-devops/devops.py health system ``` ## Requirements - Python 3.8+ (stdlib only, no external dependencies) - Docker CLI (optional — Docker sections degrade gracefully if not installed) - Standard Unix utilities (ps, ss/netstat)


Security scan verdicts — ClawScan: clean | static analysis:  | VirusTotal: suspicious | SkillSpector: suspicious (HIGH)
Skill: thomastrumpp/ztp (version 2.0.0)

--- name: ZTP description: A mandatory security audit skill for validating new code, skills, and MCP servers against the SEP-2026 Zero Trust protocol. --- # openclaw-security ## Description This skill enforces the **SEP-2026 Security Protocol**. It provides tools to audit source code for malicious patterns, obfuscation, and unauthorized network capability. It is the **Gatekeeper**; no external code (Skills, MCP Servers, Python scripts) should be integrated without passing this audit. ## Usage Use this skill whenever you need to: 1. **Audit** a new Python file, Skill, or MCP Server before using or installing it. 2. **Verify** the safety of a downloaded script. 3. **Check** for supply chain attacks (typosquatting). ## Commands ### 1. Deep Audit (Source Code) Run the **Shield Pro 2.0** static analyzer on a target directory or file. ```bash python3 skills/openclawSecurity/scripts/shield_pro.py --target <path_to_scan> --format json ``` **Output:** A JSON report containing `CRITICAL`, `HIGH`, and `MEDIUM` findings. **Action:** - If `CRITICAL` or `HIGH` > 0: **REJECT** the code. - If `MEDIUM` > 0: **HALT** and ask User for manual review. ### 2. Supply Chain Check Check `requirements.txt` or `package.json` for typosquatting and version pinning issues. ```bash python3 skills/openclawSecurity/scripts/shield_pro.py --target <path_to_requirements> --mode supply-chain ``` ### 3. Layer 2: External Defense Arsenal (Recommended) If available in the environment, the Agent MUST run these SOTA tools to augment Shield Pro's findings: | Tool | Purpose | Command | | :------------ | :---------------------------------------------- | :---------------------------------------------- | | **Bandit** | Python Static Analysis (Common Vulnerabilities) | `bandit -r <target_dir> -f json` | | **Safety** | Python Dependency Check (Known CVEs) | `safety check -r requirements.txt --json` | | **NPM Audit** | Node.js Dependency Check | `npm audit --json` (in package dir) | | **Trivy** | Filesystem/Container Scan (Secrets/Vulns) | `trivy fs <target_dir> --format json` | | **Garak** | LLM/Prompt Injection Testing | `garak --model_type <type> --model_name <name>` | > **Note:** If a tool is missing, log a warning in the final report but proceed with `shield_pro` findings. ## Workflow: The SEP-2026 Gatekeeper Process 1. **Acquire**: Download or locate the target code. 2. **Isolate**: ensure the code is not executed. 3. **Scan**: Run `shield_pro.py` on the target. 4. **Evaluate**: - **Pass**: No Critical/High issues. - **Fail**: Any Critical/High issue found. Reporting potential Line of Code (LOC) and threat type. 5. **Report**: Present the findings to the user. ## Principles - **Zero Trust**: treat all input as malicious. - **No Execution**: Never run the target code during the audit. - **Paranoia**: False positives are better than missed malware.


Security scan verdicts — ClawScan: suspicious | static analysis:  | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: ivangdavila/gif (version 1.0.1)

--- name: GIF slug: gif version: 1.0.1 description: Find, search, and create GIFs with proper optimization and accessibility. changelog: Declare required binary (ffmpeg), document optional deps (gifsicle, API keys) metadata: {"clawdbot":{"emoji":"🎞️","requires":{"bins":["ffmpeg"]},"os":["linux","darwin","win32"]}} --- ## Requirements **Required for creating GIFs:** - `ffmpeg` — video to GIF conversion **Optional:** - `gifsicle` — post-optimization (reduces size 30-50%) - `GIPHY_API_KEY` — for Giphy search API - `TENOR_API_KEY` — for Tenor search API ## Where to Find GIFs | Site | Best for | API | |------|----------|-----| | **Giphy** | General, trending | Yes (key required) | | **Tenor** | Messaging apps | Yes (key required) | | **Imgur** | Viral/community | Yes | | **Reddit r/gifs** | Niche, unique | No | ## Creating GIFs with FFmpeg **Always use palettegen (without it, colors look washed out):** ```bash ffmpeg -ss 0 -t 5 -i input.mp4 \ -filter_complex "fps=10,scale=480:-1:flags=lanczos,split[a][b];[a]palettegen[p];[b][p]paletteuse" \ output.gif ``` | Setting | Value | Why | |---------|-------|-----| | fps | 8-12 | Higher = much larger file | | scale | 320-480 | 1080p GIFs are massive | | lanczos | Always | Best scaling quality | ## Post-Optimization If `gifsicle` is available: ```bash gifsicle -O3 --lossy=80 --colors 128 input.gif -o output.gif ``` Reduces size 30-50% with minimal quality loss. ## Video Alternative For web, use video instead of large GIFs (80-90% smaller): ```html <video autoplay muted loop playsinline> <source src="animation.webm" type="video/webm"> <source src="animation.mp4" type="video/mp4"> </video> ``` ## Accessibility - **WCAG 2.2.2:** Loops >5s need pause control - **prefers-reduced-motion:** Show static image instead - **Alt text:** Describe the action ("Cat jumping off table") - **Three flashes:** Nothing >3 flashes/second (seizure risk) ## Common Mistakes - No `palettegen` in FFmpeg — colors look terrible - FPS >15 — file size explodes for no visual benefit - No lazy loading on web — blocks page load - Using huge GIF where video would work — 10x larger ## API Quick Reference **Giphy search:** ```bash curl "https://api.giphy.com/v1/gifs/search?[REDACTED_SECRET]" ``` **Tenor search:** ```bash curl "https://tenor.googleapis.com/v2/search?key=$TENOR_API_KEY&q=thumbs+up&limit=10" ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: jonathanjing/glass2claw (version 2.3.3)

--- name: glass2claw description: "Ray-Ban glasses → voice command → WhatsApp → OpenClaw auto-routes your photo into the right database. Hands-free life logging." version: "2.3.3" metadata: { "openclaw": { "emoji": "👁️", "tools": ["sessions_send", "message"] } } --- # glass2claw: From Your Eyes to Your Database — Instantly ## 🛠️ Installation ### 1. Ask OpenClaw (Recommended) Tell OpenClaw: *"Install the glass2claw skill."* The agent will handle the installation and configuration automatically. ### 2. Manual Installation (CLI) If you prefer the terminal, run: ```bash clawhub install glass2claw ``` You're wearing your **Meta Ray-Ban glasses**. You see a wine label, a business card, a tea tin. You say: > *"Hey Meta, take a picture and send this to myself on WhatsApp."* That's it. OpenClaw does the rest. The photo lands in your WhatsApp. OpenClaw's Vision Router picks it up, classifies what it is, and writes a structured entry into the right database — wine cellar, contacts, tea collection, whatever you've set up. **No typing. No app switching. No friction.** --- ## 📸 How It Works ``` Meta Ray-Ban glasses → "Hey Meta, take a picture and send this to myself on WhatsApp" → Meta AI delivers the photo to your WhatsApp → OpenClaw (WhatsApp session) receives the image → classifies intent: Wine | Tea | Contacts | Cigar | ... → routes to the matching specialist agent → writes structured entry to your database ``` Your only action is the voice command. Everything downstream is automatic. --- ## 🔧 What You Need to Set Up This skill is a **routing protocol** — it defines the pattern, not the specific implementation. You bring your own: - **Meta AI + WhatsApp connection** — enable Meta AI on your Ray-Ban glasses and link it to WhatsApp (one-time setup in the Meta View app) - **OpenClaw with WhatsApp channel** — your OpenClaw instance needs a WhatsApp session to receive the incoming images - **Destination databases** — connect whichever databases you want: Notion, Airtable, a local file, a Discord channel. The skill routes to wherever you configure it - **Database credentials** — set up API access for your chosen database yourself (Notion API key, Airtable token, etc.) > The skill templates in this package show one reference implementation using Notion + Discord. Adapt them to your own stack. --- ## 🔒 Privacy This skill processes **photos from your personal camera**. Images flow from WhatsApp → your OpenClaw instance → your configured destination. Any external services you connect (Notion, Discord, etc.) are governed by their own privacy policies. All routing logic runs on your own OpenClaw instance. --- ## 📦 What's Included - `SAMPLE_AGENT.md` — reference routing logic for the hub agent - `SAMPLE_SOUL_WINE.md` — reference persona for a wine specialist agent Use these as starting points. Customize for your own categories and destinations. --- *Created by JonathanJing | AI Reliability Architect*


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: wanan9812/rss-summarizer (version 1.0.0)

--- name: rss-summarizer description: 智能 RSS 订阅与摘要。用于订阅、抓取、过滤和摘要 RSS/Atom 订阅源。当用户需要跟踪新闻、博客更新并提供摘要时使用。 --- # RSS Summarizer Skill 本技能提供 RSS 订阅源管理、抓取和摘要功能。 ## 何时使用 - 用户希望订阅某个 RSS/Atom feed - 需要定期获取最新内容并摘要 - 需要根据关键词过滤内容 - 需要将更新推送到聊天或保存为文档 ## 可用脚本 - `scripts/add.js` - 添加订阅源 - `scripts/list.js` - 列出所有订阅源 - `scripts/remove.js` - 删除订阅源 - `scripts/fetch.js` - 抓取最新内容并摘要 - `scripts/configure.js` - 配置参数（摘要模式、语言、最大条目、过滤器） ## 使用方法 AI 在响应用户请求时，应调用相应的脚本，传入 JSON 参数（通过 stdin），并返回 JSON 结果。 脚本通用输入/输出格式： **输入 (stdin)**: ```json { "context": { "send": function } // 可选，用于通知用户 ... 具体参数（见各脚本） } ``` **输出 (stdout)**: ```json { "success": true, "message": "...", "data": { ... } } ``` ### 示例 用户说：“订阅 Hacker News 的 RSS” AI 调用 `scripts/add.js`: ```json { "url": "https://news.ycombinator.com/rss", "name": "Hacker News" } ``` AI 收到响应后向用户确认。 ## 数据存储 脚本使用 `data/subscriptions.json` 和 `data/config.json` 存储数据。首次运行会自动创建。 ## 备注 - 抓取时若网络错误会返回 `error` 字段。 - 摘要功能依赖外部 AI 服务（通过 oracle CLI），如需高级摘要可扩展。 - 支持多语言输出，默认中文。


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