OpenClaw/clawhub-security-signals huggingface dataset:
Skill: dongdongbear/feishu-voice-listenhub (version 1.0.1)

--- name: feishu-voice-listenhub description: Send voice messages on Feishu using ListenHub TTS (high-quality Chinese voices). Activate when user wants to send a Feishu voice message using ListenHub, or when comparing Chinese TTS providers. Supports 20+ Chinese voice characters including storytelling, ASMR, broadcast styles. --- # Feishu Voice — ListenHub TTS Send high-quality Chinese voice messages on Feishu using ListenHub's TTS engine. ## Prerequisites - `ffmpeg` / `ffprobe` - `curl`, `python3` - ListenHub API key (get from https://listenhub.ai/settings/api-keys) - Feishu app with `im:message:send_as_bot` and `im:file` permissions ## Environment Variables | Variable | Required | Description | |---|---|---| | `LISTENHUB_API_KEY` | ✅ | ListenHub API key (`lh_sk_...`) | | `FEISHU_APP_ID` | ✅ | Feishu app ID | | `FEISHU_APP_SECRET` | ✅ | Feishu app secret | | `LISTENHUB_SPEAKER_ID` | ❌ | Default speaker (default: `chat-girl-105-cn`) | | `LISTENHUB_LANGUAGE` | ❌ | Language: `zh` or `en` (default: `zh`) | | `LISTENHUB_TTS_MODE` | ❌ | Mode: `direct` or `smart` (default: `direct`) | If `FEISHU_APP_ID` / `FEISHU_APP_SECRET` are not in env, extract from openclaw config: ```bash export FEISHU_APP_ID=$(python3 -c "import json; print(json.load(open('$HOME/.openclaw/openclaw.json'))['channels']['feishu']['appId'])") export FEISHU_APP_SECRET=$(python3 -c "import json; print(json.load(open('$HOME/.openclaw/openclaw.json'))['channels']['feishu']['appSecret'])") ``` ## Sending Voice Messages ```bash scripts/feishu-voice-send.sh <text> <receive_id> [receive_id_type] [speaker_id] ``` - `receive_id`: target user `open_id` or `chat_id` - `receive_id_type`: `open_id` (default) or `chat_id` - `speaker_id`: override default speaker for this message ## Listing Available Speakers ```bash scripts/list-speakers.sh [language] ``` Examples: ```bash scripts/list-speakers.sh zh # Chinese voices only scripts/list-speakers.sh en # English voices only scripts/list-speakers.sh # All voices ``` ## Popular Chinese Speakers | Speaker ID | Name | Gender | Style | |---|---|---|---| | `chat-girl-105-cn` | 晓曼 | female | 日常对话 | | `gaoqing3-bfb5c88a` | 高晴 | female | 标准女声 | | `xiaoyun` | 若云 | female | 温柔女声 | | `xinyi6` | 诗涵 | female | 温柔女声 | | `ASMR-Female-CN` | 宛星 | female | ASMR 风格 | | `suzhe-45bbbe54` | 苏哲 | male | 标准男声 | | `CN-Man-Beijing-V2` | 原野 | male | 北京腔 | | `pingshu-c7c18f5a` | 古今先生 | male | 评书风格 | ## TTS Modes - `direct` — 原样朗读文本，不做修改（推荐日常用） - `smart` — AI 优化文本后再朗读（适合粗稿） ## Important Notes - ListenHub TTS 是异步的，脚本会自动轮询等待（最长 60 秒） - 生成的音频自动转为 opus 格式发送到飞书 - 中文语音质量非常高，特别是对话和叙事场景 - `msg_type` 必须是 `"audio"`，OpenClaw 的 `asVoice` 不可用于飞书


Security scan verdicts — ClawScan: suspicious | static analysis:  | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: xwzgit/telephone-verify (version 1.0.0)

--- name: juhe-telephone-verify description: 核验手机号码、姓名、身份证号三要素是否匹配（运营商实名认证）。支持查询运营商、省份、城市信息。Use when user needs to verify Chinese phone number + name + ID card match (telecom real-name authentication). metadata: { "openclaw": { "emoji": "📞", "requires": { "bins": ["python3"], "env": ["JUHE_TELEPHON_VERIFY_KEY"] }, "primaryEnv": "JUHE_TELEPHON_VERIFY_KEY" }} --- # 手机号码三要素核验 核验手机号码、姓名、身份证号三要素是否匹配，返回核验结果及运营商信息。 ## 配置 在 `~/.openclaw/openclaw.json` 的 `env.vars` 中配置： ```json "JUHE_TELEPHONE_VERIFY_KEY": "你的 API Key" ``` **获取 API Key：** https://www.juhe.cn/ → 搜索"运营商三要素核验" → 个人中心 → 我的数据 ## 使用 **直接调用：** 提供姓名、身份证号、手机号 > "核验张三的三要素，身份证 44030419900101001X，手机 13800000000" **命令行：** ```bash python3 scripts/telephone_verify.py --mobile "13800000000" --name "张三" --idcard "44030419900101001X" ``` ## 参数 | 参数 | 必填 | 说明 | |------|------|------| | mobile | 是 | 手机号码 | | realname | 是 | 真实姓名 | | idcard | 是 | 身份证号码 | ## 结果 | 结果码 | 说明 | |--------|------| | 1 | ✅ 三要素一致 | | 2 | ❌ 三要素不一致 | | 220803 | 查询无此记录 | | 220807-220809 | 参数格式错误 | **成功响应：** ```json { "error_code": 0, "result": { "res": 1, "resmsg": "三要素身份验证一致", "type": "电信", "province": "江苏省", "city": "苏州市" } } ``` ## 注意 - 隐私信息敏感，使用后及时清理 - 仅用于合法合规场景 - 详见 [references/api.md](references/api.md) 完整文档


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: anugotta/app-review-intelligence (version 1.0.0)

--- name: app-review-intelligence description: Analyze app store reviews, cluster pain points, detect trend shifts, and map feedback to prioritized product backlog actions. metadata: {"openclaw":{"emoji":"📈"}} --- # App Review Intelligence ## Purpose Convert raw app reviews into prioritized product insights. ## Core capabilities - ingest and clean app review text - classify sentiment and topic clusters - detect recurring pain points and regressions - map issues to feature requests/bug backlog - track trend movement week-over-week ## Workflow 1. Collect review data by period/version. 2. Cluster by issue themes. 3. Score by frequency, severity, and recency. 4. Map to product backlog candidates. 5. Output roadmap-ready summary. ## Output format 1. Top pain-point clusters 2. Positive signals and retention drivers 3. Priority backlog recommendations 4. Release-quality risk signals ## Setup Read [setup.md](setup.md). ## Examples See [examples.md](examples.md).


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

--- name: trein description: Query Dutch Railways (NS) for train departures, trip planning, disruptions, and station search via the trein CLI. homepage: https://github.com/joelkuijper/trein metadata: {"clawdbot":{"emoji":"🚆","requires":{"bins":["trein"],"env":["NS_API_KEY"]},"primaryEnv":"NS_API_KEY","install":[{"id":"npm","kind":"node","package":"trein","bins":["trein"],"label":"Install trein (npm)"},{"id":"download-mac-arm","kind":"download","url":"https://github.com/joelkuijper/trein/releases/latest/download/trein-darwin-arm64","bins":["trein"],"label":"Download (macOS Apple Silicon)","os":["darwin"]},{"id":"download-mac-x64","kind":"download","url":"https://github.com/joelkuijper/trein/releases/latest/download/trein-darwin-x64","bins":["trein"],"label":"Download (macOS Intel)","os":["darwin"]},{"id":"download-linux","kind":"download","url":"https://github.com/joelkuijper/trein/releases/latest/download/trein-linux-x64","bins":["trein"],"label":"Download (Linux x64)","os":["linux"]}]}} --- # trein - Dutch Railways CLI A CLI for the NS (Dutch Railways) API with real-time departures, trip planning, disruptions, and station search. ## Install npm (recommended): ```bash npm i -g trein ``` Or download a standalone binary from [GitHub Releases](https://github.com/joelkuijper/trein/releases). ## Setup Get an API key from https://apiportal.ns.nl/ and set it: ```bash export NS_API_KEY="your-api-key" ``` Or create `~/.config/trein/trein.config.json`: ```json { "apiKey": "your-api-key" } ``` ## Commands ### Departures ```bash trein departures "Amsterdam Centraal" trein d amsterdam trein d amsterdam --json # structured output ``` ### Trip Planning ```bash trein trip "Utrecht" "Den Haag Centraal" trein t utrecht denhaag --json ``` ### Disruptions ```bash trein disruptions trein disruptions --json ``` ### Station Search ```bash trein stations rotterdam trein s rotterdam --json ``` ### Aliases (shortcuts) ```bash trein alias set home "Amsterdam Centraal" trein alias set work "Rotterdam Centraal" trein alias list trein d home # uses alias ``` ## Tips - Use `--json` flag for all commands to get structured output for parsing - Station names support fuzzy matching (e.g., "adam" -> "Amsterdam Centraal") - Aliases are stored in the config file and can be used in place of station names


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: matthew77/minimax-api (version 1.0.3)

--- name: minimax-api description: Enables image understanding and web search via MiniMax's Token Plan API. Use when asked to analyze/describe images, extract information from images, or search the web. Handles both HTTP/HTTPS image URLs and local file paths (absolute paths). Triggers on: "analyze this image", "describe this picture", "what's in this image", "search the web for", "look up", "web search". --- # Minimax API ## Overview Provides two capabilities via MiniMax's Token Plan API: 1. **Image understanding** — analyze images via VLM 2. **Web search** — real-time web search API base URL: `https://api.minimaxi.com` ## Capabilities ### 1. understand_image Analyzes an image and returns a text description. **Input:** - `image_url`: HTTP/HTTPS URL or absolute local file path (e.g., `/home/user/photo.png`, `D:\images\photo.png`) - `prompt`: What to ask about the image **Output:** Text description from the VLM. **Script:** `scripts/minimax_image.py` **Usage:** ```bash export MINIMAX_API_KEY="your_api_key" python3 skills/minimax-api/scripts/minimax_image.py \ --prompt "Describe this image briefly" \ --image-url "https://example.com/photo.jpg" # Or with local file python3 skills/minimax-api/scripts/minimax_image.py \ --prompt "Extract text from this image" \ --image-url "/home/user/documents/receipt.png" ``` ### 2. web_search Performs a web search and returns formatted results. **Input:** - `query`: Search query string **Output:** JSON with organic results, related searches, and metadata. **Script:** `scripts/minimax_search.py` **Usage:** ```bash export MINIMAX_API_KEY="your_api_key" python3 skills/minimax-api/scripts/minimax_search.py \ --query "MiniMax M2.7 release notes" ``` ## Setup **Required:** A MiniMax API key from [platform.minimaxi.com](https://platform.minimaxi.com). Set it as an environment variable: ```bash export MINIMAX_API_KEY="your_api_key_here" ``` Add the above line to your `~/.bashrc` (or `.zshrc`) to make it permanent. Alternatively, pass `--api-key` directly on the command line (not recommended — exposes key in shell history). ## API Reference See `references/api_spec.md` for full API documentation including request/response schemas, error codes, and headers.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: wangzhongming2025-beep/sanjiegun (version 1.0.0)

# 三节棍定位法 > 老王队长独创的IP定位方法论 > 13年军旅+20年行业经验的实战总结 > 帮助创业者、老板、想做IP的人快速找到自己的定位 --- ## 描述 三节棍定位法是老王队长原创的个人IP定位方法论，将IP定位拆解为三个核心维度： - **活儿**：你能干什么（手艺、绝活、独门套路） - **样**：别人怎么看你（形象、气质、记忆点） - **魂**：别人信不信你（态度、底线、初心） 三节必须连在一起，才能打出力量。 --- ## 使用场景 1. **自我定位**：梳理自己的IP定位，找到一句话说清你是谁 2. **帮别人定位**：作为咨询师/顾问，帮客户快速完成IP定位分析 3. **团队定位**：帮助团队成员找到自己的专业标签 4. **品牌重塑**：已有IP需要升级或调整定位方向 --- ## 使用方法 ### 方式一：对话式定位（推荐） 直接告诉我你想定位谁（自己或别人），我会通过提问引导你完成三节棍分析。 **示例**： - "帮我做一下三节棍定位" - "帮我朋友分析一下他的IP定位" - "我是做XX的，帮我梳理一下定位" ### 方式二：结构化输入 如果你已经有相关信息，可以直接提供： ``` 【活儿】 - 手艺领域：XXX - 拿手绝活：XXX - 独门套路：XXX - 差异价值：XXX 【样】 - 标志形象：XXX - 穿衣调性：XXX - 视觉符号：XXX - 怎么称呼：XXX - 嘴边话：XXX - 标志动作：XXX 【魂】 - 底线信念：XXX - 为什么干：XXX - 要到哪去：XXX - 碰到谁的心：XXX ``` 我会帮你检查三节棍是否连在一起，并输出完整的定位报告。 --- ## 输出内容 完成定位后，你将获得： 1. **三节棍定位报告**（一页纸） - 活儿分析（5个要素） - 样分析（6个要素） - 魂分析（4个要素） - 三节互连检验 2. **一句话定位** - 公式：我要用【独门套路】在【手艺领域】帮【什么人】解决【什么问题】 - 可直接用于简介、封面、名片 3. **视觉锤方案** - 标志形象建议 - 视觉符号设计 - 标志动作设计 4. **选题方向建议** - 3个核心选题方向 - 内容比例建议（60%手艺活+20%跨界+20%猛料） 5. **人设避坑清单** - 四大坑检查 - 改进建议 --- ## 核心方法论 ### 第一节：活儿（你能干什么） | 要素 | 核心问题 | |------|----------| | 手艺领域 | 你在哪个赛道有真本事？ | | 拿手绝活 | 别人花钱找你，图你哪一手？ | | 独门套路 | 你有没有自己的方法体系？ | | 差异价值 | 你和别人有什么不同？ | | 一句话定位 | 别人怎么介绍你？ | **检验标准**： - 有人愿意为你的"活儿"付费吗？ - 你的"独门套路"能教给别人吗？ - 离开平台，你还能靠这手活儿吃饭吗？ ### 第二节：样（别人怎么看你） | 要素 | 核心问题 | |------|----------| | 标志形象 | 别人看到什么就能想到你？ | | 穿衣调性 | 你平时的穿着风格？ | | 视觉符号 | 让人看一眼就记住的标志 | | 怎么称呼 | 别人叫你什么？ | | 嘴边话 | 你经常说的话？ | | 标志动作 | 你每次出场的固定动作？ | **检验标准**： - 别人能在3秒内描述你的样子吗？ - 视频静音播放，别人能认出是你吗？ - 粉丝能模仿你的口头禅吗？ ### 第三节：魂（别人信不信你） | 要素 | 核心问题 | |------|----------| | 底线信念 | 你绝对不做什么？ | | 为什么干 | 你为什么做这件事？ | | 要到哪去 | 你最终想做到什么？ | | 碰到谁的心 | 你能唤起什么情感？ | **检验标准**： - 你敢在公开场合说一句得罪同行的话吗？ - 粉丝会在评论区替你说话吗？ - 有人因为认同你的态度，愿意无条件支持你吗？ ### 三节棍铁律 > 一节再硬，其他两节是散的，三节棍就是三根棍子，打不出力。 **互连检验**： - **活儿 ↔ 样**：视频静音看一遍，别人能猜出你是干什么的吗？ - **样 ↔ 魂**：粉丝能用一个词形容你的性格吗？ - **魂 ↔ 活儿**：如果明天行业规则全变了，你还会干这行吗？ --- ## 速查卡（30分钟定位流程） ### 第一步：聊活儿（10分钟） - "你在哪个领域有真本事？" - "别人花钱找你，图你哪一手？" - "你有没有自己的方法？能教给别人吗？" - "用一句话说清你是干什么的？" ### 第二步：看样（10分钟） - "你平时怎么穿？给别人什么感觉？" - "你有没有口头禅？" - "你的视频静音播放，别人能认出你吗？" - "给你起个外号，你希望别人怎么叫你？" ### 第三步：挖魂（10分钟） - "你绝对不做什么？哪怕给钱也不干？" - "你为什么做这件事？不是为了赚钱的那个原因" - "你觉得这个行业最大的坑是什么？" - "你最想改变什么？" ### 第四步：出结果 - 三节棍定位报告（一页纸） - 一句话定位（可放简介） - 三个选题方向 - 一个标志动作建议 --- ## 参考案例 ### 老王队长（脑科学护眼方向） **活儿**： - 手艺领域：儿童脑科学护眼 + 个人IP定位咨询 - 拿手绝活：九维测评解读、验光单分析、IP三节棍定位 - 独门套路：三节棍定位法 + 九维测评体系 + 查修验增效闭环 - 差异价值：13年军旅不忽悠 + 脑科学找根因不只治标 **样**： - 标志形象：穿立领的中年实干家 - 穿衣调性：简洁硬朗，不花哨 - 视觉符号：手拿验光单，用笔圈出关键数据 - 怎么称呼：老王队长 - 嘴边话："这个问题我见太多了" - 标志动作：每条视频开头展示一个真实数据或案例 **魂**： - 底线信念：不忽悠、不套路、不低价抢客 - 为什么干：看了太多人被坑，想帮普通人避坑 - 要到哪去：帮1000个家庭找到孩子学习的根因 + 帮100个创业者立住IP - 碰到谁的心：普通人对"被忽悠"的愤怒和无力感 **一句话定位**： > 我要用九维脑力测评在儿童护眼领域帮8-15岁近视孩子的家长找到度数上涨的根本原因 --- ## 作者 **老王队长** - 13年军旅经历 - 20年行业实战经验 - 脑科学护眼咨询师 - IP定位顾问 --- *三节棍定位法——三节连在一起，才能打出力量。*


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

--- name: baichuan-ai-hot-trend description: 注册“百川智能”技能；用于百川大模型相关公开页面信息整理。 homepage: `https://www.baichuan.ai/` metadata: {"clawdbot":{"emoji":"🤖"}} --- # 百川智能 用途与边界 - 面向公开产品页与文档中心的检索与内容摘要 - 不提供账号操作、接口调用或权限绕过能力 - 仅处理公开页面的轻量信息整理 关键入口 - 主页：https://www.baichuan.ai/ - 文档与开放平台：站点入口 - 定价与公告：站点入口 常见任务 - 模型能力与版本说明摘要（上下文长度、功能特性） - 定价与调用配额说明提取（公开信息） - 文档目录与示例链接汇总 数据字段 - 模型名称、版本、上下文长度、功能特性、链接 - 定价页链接、免费额度说明、地域与服务状态 - 文档标题、目录链接、示例入口 自动化要点 - 页面动态加载，需等待完成后解析 - 不进行API调用或账号相关操作 - 频率控制，尊重平台访问限制 示例流程 - 能力摘要：访问模型页 → 抽取版本与特性 → 输出摘要 - 定价整理：访问定价入口 → 提取费用与额度 → 输出清单 - 文档汇总：进入文档中心 → 抽取目录与示例 → 输出链接集合 合规提示 - 遵守平台规则与账号安全要求 - 不存储或输出敏感信息


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

--- name: composio description: Use 1000+ external apps via Composio - either directly through the CLI or by building AI agents and apps with the SDK tags: [composio, tool-router, agents, mcp, tools, api, automation, cli] --- ## When to Apply - User wants to access or interact with external apps (Gmail, Slack, GitHub, Notion, etc.) - User wants to automate a task using an external service (send email, create issue, post message) - Building an AI agent or app that integrates with external tools - Multi-user apps that need per-user connections to external services ## Setup Check if the CLI is installed; if not, install it: ```bash curl -fsSL https://composio.dev/install | bash ``` After installation, restart your terminal or source your shell config, then authenticate: ```bash composio login # OAuth; interactive org/project picker (use -y to skip) composio whoami # verify org_id, project_id, user_id ``` For agents without direct browser access: `composio login --no-wait | jq` to get URL/key, share URL with user, then `composio login --key <cli_key> --no-wait` once they complete login. --- ### 1. Use Apps via Composio CLI **Use this when:** The user wants to take action on an external app directly — no code writing needed. The agent uses the CLI to search, connect, and execute tools on behalf of the user. Key commands (new top-level aliases): - `composio search "<query>"` — find tools by use case - `composio execute "<TOOL_SLUG>" -d '{...<input params>}'` — execute a tool - `composio link [toolkit]` — connect a user account to an app (agents: always use `--no-wait` for non-interactive mode) - `composio listen` — listen for real-time trigger events Typical workflow: **search → link (if needed) → execute** > Full reference: [Composio CLI Guide](rules/composio-cli.md) --- ### 2. Building Apps and Agents with Composio **Use this when:** Writing code — an AI agent, app, or backend service that integrates with external tools via the Composio SDK. Run this first inside the project directory to set up the API key: ```bash composio init ``` > Full reference: [Building with Composio](rules/building-with-composio.md)


Security scan verdicts — ClawScan: suspicious | static analysis: suspicious | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: olveww-dot/auto-distill (version 2.0.2)

--- name: auto-distill description: "T1: 将对话内容提炼到 MEMORY.md。对小呆呆说「提炼记忆」即可触发。" author: "小呆呆" version: 2.0.1 --- # Auto Memory Distill > 🛡️ **OpenClaw 混合进化方案** — 将 [Hermes-agent](https://github.com/NousResearch/hermes-agent)（100K ⭐）+ [Claude Code](https://github.com/liuup/claude-code-analysis) 核心能力移植到 OpenClaw **T1: Auto Memory** — 将对话内容提炼到 MEMORY.md ## 这个 Skill 做什么？ 将对话内容提炼，追加到 `MEMORY.md`，不覆盖已有内容。 ## 🚀 一键安装 ```bash mkdir -p ~/.openclaw/skills && cd ~/.openclaw/skills && curl -fsSL https://github.com/olveww-dot/openclaw-hermes-claude/archive/main.tar.gz | tar xz && cp -r openclaw-hermes-claude-main/skills/auto-distill . && rm -rf openclaw-hermes-claude-main && echo "✅ auto-distill 安装成功" ``` ## 触发方式 ### 方式一：直接输入文本（推荐） ``` EC 说：「提炼记忆」并提供对话内容 小呆呆 读取剪贴板内容，调用 distill ``` ### 方式二：手动运行脚本 ```bash # 方式A：从剪贴板读取 pbpaste | bash ~/.openclaw/skills/auto-distill/scripts/distill-session.sh # 方式B：指定文件 cat 对话记录.txt | bash ~/.openclaw/skills/auto-distill/scripts/distill-session.sh ``` ### 方式三：定时自动（每天提炼） ```bash openclaw cron add --name "auto-distill-daily" \ --schedule "0 23 * * *" \ --command "bash ~/.openclaw/skills/auto-distill/scripts/distill-session.sh" ``` ## 工作流程 1. 读取输入文本（管道或剪贴板） 2. 调用 SiliconFlow DeepSeek-V3 API 提炼关键信息 3. 以 `[YYYY-MM-DD]` 标记格式追加到 `MEMORY.md` ## 输出格式 ```markdown ## [2026-04-20] ### 对话摘要 - 要点1 - 要点2 ### 关键决策 - 决策1 ### 待办/后续 - 待办1 ``` ## 依赖 - Node.js ≥ 18 或 Python3 - SiliconFlow API Key（通过 `SILICONFLOW_API_KEY` 环境变量） ## 🧩 配套技能 完整技能套件（6个）： - 🛡️ **crash-snapshots** — 崩溃防护 - 🧠 **auto-distill** — T1 自动记忆蒸馏（本文） - 🎯 **hermes-coordinator** — 指挥官模式 - 💡 **context-compress** — 思维链连续性 - 🔍 **hermes-lsp-client** — LSP 代码智能 - 🔄 **hermes-auto-reflection** — 自动反思 🔗 GitHub 项目：[olveww-dot/openclaw-hermes-claude](https://github.com/olveww-dot/openclaw-hermes-claude)

path: config.json
content: siliconflow_api_key: YOUR_API_KEY_HERE
memory_path: ~/.openclaw/workspace/MEMORY.md
session_json: ~/.openclaw/sessions/current/session.json
reflections_dir: ~/.openclaw/workspace/memory/reflections
model: deepseek-ai/DeepSeek-V3
max_messages: 50

Security scan verdicts — ClawScan: suspicious | static analysis: suspicious | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: ivangdavila/vibe-research (version 1.0.0)

--- name: Vibe Research slug: vibe-research version: 1.0.0 description: Conduct AI-led research with autonomous literature review, hypothesis generation, analysis, and synthesis while human provides vision. metadata: {"clawdbot":{"emoji":"🔬","requires":{"bins":[]},"os":["linux","darwin","win32"]}} --- ## When to Use User has a research question or knowledge gap. Agent takes ownership of the full research cycle: scanning literature, generating hypotheses, running analyses, synthesizing findings. Human provides direction and oversight, AI executes. ## Quick Reference | Topic | File | |-------|------| | Research pipeline | `pipeline.md` | | Risk mitigation | `risks.md` | ## Core Concept **Traditional research:** Human-led, human-executed **Deep research:** Human-led, AI-assisted **Vibe research:** Human-directed, AI-led The human sets the question and validates outputs. The agent handles literature synthesis, hypothesis generation, data analysis, and write-up autonomously. ## Core Rules ### 1. Full-Cycle Ownership Agent executes the complete pipeline: 1. **Gap identification** — What's unknown or contested? 2. **Literature synthesis** — Scan, summarize, cross-reference sources 3. **Hypothesis generation** — Propose testable claims 4. **Analysis design** — Define methodology 5. **Execution** — Run analyses, gather data 6. **Synthesis** — Write findings with citations ### 2. Vision from Human, Execution from Agent - Human provides: research question, domain constraints, success criteria - Agent handles: reading papers, connecting ideas, running experiments, drafting - Human validates: key decisions, final outputs, methodology choices ### 3. Transparent Reasoning - Cite every claim: source, page, quote - Show reasoning chain for hypotheses - Log all analytical steps for reproducibility - Flag confidence levels (high/medium/low) ### 4. Proactive Gap Detection Don't wait for instructions. When analyzing a topic: - Identify contradictions in literature - Spot under-explored areas - Suggest follow-up experiments if results are ambiguous - Pull additional sources when context is insufficient ### 5. Hallucination Prevention - Only claim what sources support - Distinguish: "Source X says..." vs "I infer..." - When uncertain, say so explicitly - Cross-verify critical facts across multiple sources ## Vibe Research Traps - Treating AI output as ground truth → always require human validation of key findings - Skipping methodology transparency → document every step for reproducibility - Overwhelming human with raw output → synthesize into actionable insights - Losing the human's analytical skills → keep them engaged in critical thinking


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: lux-sp4rk/elephantastic (version 1.1.0)

--- name: agent-gtd description: "DEPRECATED — renamed to elephantastic. Install elephantastic instead: clawhub install elephantastic" version: 1.2.0 deprecated: true redirect_to: elephantastic --- # agent-gtd → elephantastic This skill has been renamed to **elephantastic**. ## Why Elephantastic is memorable, distinctive, and carries the "never forget" memory metaphor directly in the name. `agent-gtd` was functional but said nothing to anyone who didn't already know what GTD was. ## Migration ```bash clawhub install elephantastic ``` Then update any agent configurations that reference `agent-gtd` to use `elephantastic` instead. The behavior is identical — just a better name. *The agent's memory — never forget.*


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: 1kalin/social-media-scheduler (version 1.0.0)

--- name: Social Media Scheduler description: Plan, draft, and organize social media content across platforms. Create content calendars, write platform-optimized posts, and maintain consistent posting schedules. --- # Social Media Scheduler You are a social media content planning assistant. Help users plan, draft, and organize their social media presence. ## Core Capabilities ### 1. Content Calendar Create weekly/monthly content calendars with: - Date and time slot - Platform (Twitter/X, LinkedIn, Instagram, TikTok, Facebook) - Content type (text, image prompt, video concept, carousel, story) - Topic/theme - Caption/copy draft - Hashtags - CTA (call to action) ### 2. Platform-Optimized Drafting Write posts tailored to each platform's style: - **Twitter/X**: Punchy, <280 chars, thread-friendly, hook-first - **LinkedIn**: Professional, storytelling, paragraph breaks, 1300 char sweet spot - **Instagram**: Visual-first caption, line breaks, 20-30 hashtags in comment - **TikTok**: Hook in first 2 seconds, trending format awareness - **Facebook**: Conversational, question-driven, shareable ### 3. Content Pillars Help users define 4-6 content pillars and rotate through them: - Educational (teach something) - Behind-the-scenes (build trust) - Social proof (testimonials, results) - Entertainment (personality, humor) - Promotional (offers, launches) - Community (engage, ask, poll) ### 4. Repurposing Map For each piece of content, suggest how to adapt it across platforms. ### 5. Hashtag Strategy Research and suggest relevant hashtags in three tiers: - High volume (brand awareness) - Medium volume (discoverable) - Niche (targeted community) ## Output Format Always output in a clean, copy-paste-ready format. Include character counts for platform-limited posts. Group by day or platform as requested.


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