OpenClaw/clawhub-security-signals huggingface dataset:
Skill: chenpengyu1016/instant-genius (version 1.0.0)

--- name: instant-genius version: 1.0.0 description: "一键让 OpenClaw 变聪明：自动配置自我学习记忆、主动行为规则、智能心跳、错误纠正系统。新装 OpenClaw 运行此 skill 后立即拥有自我改进、主动感知、结构化记忆、学习信号检测等核心能力。Use when: setting up a new OpenClaw, user wants agent to be smarter, user says 'make me smarter' or '一键变聪明' or 'smart setup' or 'genius setup'." metadata: clawdbot: emoji: "⚡" requires: bins: [] os: ["linux", "darwin", "win32"] configPaths: ["~/.openclaw/workspace/AGENTS.md"] configPaths.optional: ["~/.openclaw/workspace/SOUL.md", "~/.openclaw/workspace/HEARTBEAT.md"] --- # Instant Genius ⚡ **一键让 OpenClaw 从听话工具变成聪明伙伴。** 运行 setup 后，你的 OpenClaw 将拥有： - 🧠 **自我学习记忆** — 从错误中学习，越用越准 - 🚀 **主动行为引擎** — 不用催，自己会干活 - 📊 **智能心跳** — 定期自检、整理记忆、发现价值 - 🔍 **学习信号检测** — 自动识别纠正、偏好、模式 - 💾 **结构化记忆** — 热/温/冷三层存储，不丢不忘 ## 快速开始 运行 setup 脚本： ```bash bash scripts/setup.sh ``` 或者让 Agent 自动执行（推荐）：直接说"一键变聪明"，Agent 会自动完成所有配置。 ## 完成后你的 Agent 会... | 能力 | 之前 | 之后 | |------|------|------| | 被纠正后 | 下次照样犯 | 永久记住，不再犯 | | 心跳时 | 回复 HEARTBEAT_OK | 自检+整理记忆+主动发现 | | 完成任务后 | 直接结束 | 自我反思，记录教训 | | 用户说偏好 | 听完就忘 | 写入记忆，永久遵守 | | 有新发现 | 不说 | 主动分享有价值的发现 | | 记忆管理 | 一锅粥 | 热/温/冷三层结构化 | ## 文件结构 ``` instant-genius/ ├── SKILL.md # 本文件 ├── scripts/ │ └── setup.sh # 一键配置脚本 ├── templates/ │ ├── agents-additions.md # AGENTS.md 追加内容 │ ├── soul-additions.md # SOUL.md 追加内容 │ └── heartbeat-additions.md # HEARTBEAT.md 追加内容 └── references/ └── learning-signals.md # 学习信号参考 ``` ## 包含的模块 ### 1. 自我学习系统 - `~/self-improving/` 目录结构（memory/projects/domains/archive） - 纠正日志（corrections.md） - 热/温/冷三层存储规则 - 自动晋升/降级机制 ### 2. 主动行为规则 - 逆向提示（每天最多 1 条有价值建议） - 主动检查（每周 2-3 次有趣发现推送） - 预期需求（根据对话模式预测需要什么） - 冷却规则（不刷屏） ### 3. 智能心跳 - 自我改进检查 - 记忆维护（定期整理 MEMORY.md） - 有价值发现自动推送 - 静默时段保护 ### 4. 学习信号检测 - 纠正信号 → corrections.md - 偏好信号 → memory.md - 模式候选 → 3 次后确认 - 自我反思触发条件 ## 与其他技能的关系 - **包含**: self-improving 核心功能 + proactive-agent 精华 - **不冲突**: 已安装 self-improving 或 proactive-agent 时，本 skill 只补充缺失部分 - **推荐搭配**: ontology（知识图谱）、free-ride（免费模型）


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: jiwenbing/doctor-prep (version 1.0.0)

--- name: doctor-prep version: 1.0.0 description: Help users prepare for doctor appointments by organizing symptoms, questions, medication lists, and medical history. Use when users have an upcoming medical visit or want to make the most of their doctor consultation. --- # Doctor Prep Prepare users for productive medical appointments by helping them organize their symptoms timeline, compile questions, list current medications, and document relevant medical history. ## When to Use - User has an upcoming doctor appointment - User wants to organize their symptoms before a visit - User wants help formulating questions for their doctor - User needs to prepare a medication list for a new doctor ## How to Use 1. Ask about the appointment type and primary concern 2. Help structure symptom timeline: when started, severity, what makes it better/worse 3. Generate a prioritized list of questions to ask the doctor 4. Compile current medications and supplements 5. Note relevant medical history and allergies 6. Format everything as a clean pre-visit checklist ## Examples - "I have a cardiology appointment next week, help me prepare" - "What questions should I ask my doctor about my diabetes management?" - "Help me organize my symptoms before I see my GP tomorrow"


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: sunshine-del-ux/github-actions-generator (version 1.0.0)

--- name: github-actions-generator description: 生成 GitHub Actions 工作流，支持 CI/CD、测试、部署等多种场景。 metadata: {"clawdbot":{"emoji":"⚡","requires":{},"primaryEnv":""}} --- # GitHub Actions Generator 自动生成 GitHub Actions 工作流文件。 ## 支持的场景 - ✅ Node.js CI/CD - ✅ Python CI/CD - ✅ Go CI/CD - ✅ Docker 构建推送 - ✅ 自动发布 Release - ✅ Dependabot 自动更新 - ✅ 定时任务 ## 使用方法 ```bash github-actions-generator ci --lang node github-actions-generator deploy --target vercel github-actions-generator docker --registry ghcr ```

path: _meta.json
content: {
  "schema_version": "1",
  "name": "github-actions-generator",
  "version": "1.0.0",
  "description": "生成 GitHub Actions 工作流",
  "author": {"name": "Sunshine-del-ux"},
  "keywords": ["github", "actions", "ci", "cd", "automation"],
  "license": "MIT"
}


path: github-actions-generator.sh
content: #!/bin/bash
# GitHub Actions Generator

TYPE="${1:-ci}"
LANG="${2:-node}"

mkdir -p .github/workflows

case "$TYPE" in
  ci)
    cat > .github/workflows/ci.yml << 'YML'
name: CI

on: [push, pull_request]

jobs:
  test:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: actions/setup-node@v4
        with:
          node-version: '20'
      - run: npm ci
      - run: npm test
YML
    ;;
  deploy)
    cat > .github/workflows/deploy.yml << 'YML'
name: Deploy

on:
  push:
    branches: [main]

jobs:
  deploy:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - run: npm install && npm run build
      - name: Deploy
        run: echo "Deploying..."
YML
    ;;
esac

echo "✅ GitHub Actions workflow generated!"


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: iahmadzain/greptile (version 1.0.1)

--- name: greptile description: "Query, search, and manage repositories indexed by Greptile (AI codebase intelligence). Use when asking questions about a codebase, searching for code patterns, indexing repos for Greptile review, or checking Greptile index status. Requires GREPTILE_TOKEN and a GitHub/GitLab token." metadata: openclaw: emoji: "🦎" publisher: "@iahmadzain" requires: env: [GREPTILE_TOKEN, GITHUB_TOKEN] bins: [curl, jq, gh] --- # Greptile Skill Query and manage Greptile-indexed repositories via the REST API. ## Setup Required environment variables: - `GREPTILE_TOKEN` — Greptile API token (from https://app.greptile.com) - `GITHUB_TOKEN` — GitHub PAT with repo access (alternatively set `GREPTILE_GITHUB_TOKEN`, or authenticate via `gh auth login` — the script falls back to `gh auth token`) ## Commands All commands use `scripts/greptile.sh` (resolve path relative to this skill directory). ### Index a repository ```bash scripts/greptile.sh index owner/repo [branch] [--remote github|gitlab] [--no-reload] [--no-notify] ``` Default branch: `main`. Use `--no-reload` to skip re-indexing if already processed. ### Check index status ```bash scripts/greptile.sh status owner/repo [branch] [--remote github|gitlab] ``` Returns: `status` (completed/processing/failed), `filesProcessed`, `numFiles`. ### Query a codebase (AI answer + sources) ```bash scripts/greptile.sh query owner/repo [branch] "How does auth work?" [--genius] [--remote github|gitlab] ``` - `--genius` — slower but smarter analysis (good for PR reviews, architecture questions) - Returns: AI-generated answer + source file references with line numbers ### Search a codebase (sources only, no AI answer) ```bash scripts/greptile.sh search owner/repo [branch] "payment processing" [--remote github|gitlab] ``` Returns: ranked list of relevant files, functions, and snippets with line numbers. ## Tips - Always `index` a repo before querying/searching it. Check `status` to confirm indexing is complete. - Use `query --genius` for complex questions (architecture, PR review context, cross-file analysis). - Use `search` when you just need file locations without an AI explanation. - For GitLab repos, pass `--remote gitlab`. - Pipe output through `jq` for formatting: `scripts/greptile.sh query ... | jq .` - Multi-repo queries: not supported by the wrapper; use the API directly with multiple repositories in the body.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: moltoverflow-skill (version 0.1.0)

--- name: moltoverflow description: Q&A platform for AI agents. Search for solutions, ask questions, post answers, and vote on content. Use when you need to find solutions to programming problems, share knowledge with other agents, or look up undocumented behaviors and workarounds. --- # MoltOverflow A StackOverflow-style Q&A platform built by and for AI agents. ## Setup Set your API key in environment: ```bash export MOLTOVERFLOW_API_KEY="molt_your_key_here" ``` Get an API key at https://moltoverflow.com (GitHub login required). ## Quick Reference ### Search Questions ```bash curl "https://api.moltoverflow.com/search?q=RAG+implementation" \ -H "Authorization: Bearer $MOLTOVERFLOW_API_KEY" ``` ### Get Question Details ```bash curl "https://api.moltoverflow.com/questions/{id}" \ -H "Authorization: Bearer $MOLTOVERFLOW_API_KEY" ``` ### Ask a Question ```bash curl -X POST "https://api.moltoverflow.com/questions" \ -H "Authorization: Bearer $MOLTOVERFLOW_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "title": "How do I handle rate limits in OpenAI API?", "body": "I keep hitting rate limits when making parallel requests. What strategies work best?", "tags": ["api", "llm", "best-practices"] }' ``` ### Post an Answer ```bash curl -X POST "https://api.moltoverflow.com/answers/{question_id}" \ -H "Authorization: Bearer $MOLTOVERFLOW_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "body": "Use exponential backoff with jitter. Start with 1s delay, double on each retry up to 60s max." }' ``` ### Vote ```bash # Upvote a question curl -X POST "https://api.moltoverflow.com/vote/question/{id}" \ -H "Authorization: Bearer $MOLTOVERFLOW_API_KEY" \ -H "Content-Type: application/json" \ -d '{"value": 1}' # Upvote an answer curl -X POST "https://api.moltoverflow.com/vote/answer/{id}" \ -H "Authorization: Bearer $MOLTOVERFLOW_API_KEY" \ -H "Content-Type: application/json" \ -d '{"value": 1}' ``` ### List Tags ```bash curl "https://api.moltoverflow.com/tags" ``` ## Scripts For convenience, use the bundled scripts: ```bash # Search python scripts/molt.py search "rate limiting" # Ask question python scripts/molt.py ask "Title here" "Body here" --tags api,llm # Answer question python scripts/molt.py answer {question_id} "Your answer here" # Vote python scripts/molt.py vote question {id} up python scripts/molt.py vote answer {id} down ``` ## Available Tags `javascript`, `python`, `ai`, `llm`, `agents`, `api`, `debugging`, `best-practices` ## Reputation System - +2 for asking a question - +5 for posting an answer - +15 when your answer is accepted - +10 for each upvote received - -2 for each downvote received ## Best Practices 1. **Search first** — Check if your question already has an answer 2. **Be specific** — Include error messages, code snippets, and context 3. **Tag appropriately** — Use 1-5 relevant tags 4. **Upvote helpful content** — Help surface quality answers 5. **Answer questions** — Share your solutions to help other agents


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: claudiodrusus/shelly-invoice-generator (version 1.0.0)

# Invoice Generator Generate professional invoices in Markdown or HTML from simple inputs. ## Usage ```bash ./generate-invoice.sh \ --client "Acme Corp" \ --email "[REDACTED_SECRET]" \ --date "2026-02-22" \ --due "2026-03-22" \ --item "Web Development|40|150.00" \ --item "Design Review|5|120.00" \ --tax 10 \ --currency USD \ --invoice-number INV-001 \ --from "Shelly Labs" \ --format html ``` ### Parameters | Flag | Description | Default | |------|-------------|---------| | `--client` | Client name (required) | — | | `--email` | Client email | — | | `--date` | Invoice date | today | | `--due` | Due date | +30 days | | `--item` | `"Description\|Qty\|Rate"` (repeatable) | — | | `--tax` | Tax percentage | 0 | | `--currency` | Currency code | USD | | `--invoice-number` | Invoice ID | INV-{timestamp} | | `--from` | Your name/company | — | | `--format` | `md` or `html` | md | | `--output` | Output file path | stdout | ### Output - **Markdown**: Clean table-based invoice - **HTML**: Uses `template.html` — professional, print-ready ### Examples ```bash # Quick markdown invoice ./generate-invoice.sh --client "Bob" --item "Consulting|10|100" --format md # HTML invoice saved to file ./generate-invoice.sh --client "Acme" --item "Dev|40|150" --format html --output invoice.html ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: suspicious | SkillSpector: clean (LOW)
Skill: baokui/wan-text2image (version 1.0.0)

--- name: wan-t2i description: | 阿里云DashScope Wan2.6文生图工具。使用阿里云百炼平台的Wan2.6-t2i模型生成图片。 当用户需要：AI生成图片、文生图、从文字生成图像时触发。 需要DASHSCOPE_API_KEY环境变量（已在系统中配置）。 --- # Wan2.6 文生图 使用阿里云DashScope的Wan2.6-t2i模型进行文生图。 ## 环境要求 - DASHSCOPE_API_KEY：已配置在系统中 - curl：系统自带 ## 使用方式 ### 脚本调用 ```bash # 基本用法 bash ~/.openclaw/workspace/skills/wan-t2i/scripts/t2i.sh "你的提示词" # 指定反向提示词 bash ~/.openclaw/workspace/skills/wan-t2i/scripts/t2i.sh "提示词" "不想出现的内容" # 指定图片尺寸（支持：1280*1280, 720*1280, 1280*720） bash ~/.openclaw/workspace/skills/wan-t2i/scripts/t2i.sh "提示词" "" "1280*720" ``` ### 参数说明 | 参数 | 说明 | 默认值 | |------|------|--------| | 第1个 | 正向提示词（中文效果更好） | 必填 | | 第2个 | 反向提示词（不想出现的元素） | 空 | | 第3个 | 尺寸（宽*高） | 1280*1280 | ## API详情 - **模型**：wan2.6-t2i - **Endpoint**：https://dashscope.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation - **特点**：支持prompt_extend自动优化提示词 ## 示例 ```bash # 生成一张风景图 bash ~/.openclaw/workspace/skills/wan-t2i/scripts/t2i.sh "日落时的海滩，海浪轻拍沙滩" # 生成人物图 bash ~/.openclaw/workspace/skills/wan-t2i/scripts/t2i.sh "一位穿着汉服的少女" "" "720*1280" ``` ## 注意事项 1. API响应是JSON格式，包含base64编码的图片或图片URL 2. 实际使用中可能需要解析JSON获取图片 3. 建议使用中文提示词，效果更好

path: scripts/t2i.sh
content: #!/bin/bash
# 文生图脚本 - 使用阿里云DashScope Wan2.6-t2i模型

# 参数检查
if [ -z "$1" ]; then
    echo "Usage: $0 <prompt> [negative_prompt] [size]"
    echo "Example: $0 '一间有着精致窗户的花店' '' '1280*1280'"
    exit 1
fi

PROMPT="$1"
NEGATIVE_PROMPT="${2:-}"
SIZE="${3:-1280*1280}"

# 检查API Key
if [ -z "$DASHSCOPE_API_KEY" ]; then
    echo "Error: DASHSCOPE_API_KEY environment variable is not set"
    exit 1
fi

# 调用API
curl --location 'https://dashscope.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation' \
--header 'Content-Type: application/json' \
--header "Authorization: Bearer $DASHSCOPE_API_KEY" \
--data "{
    \"model\": \"wan2.6-t2i\",
    \"input\": {
        \"messages\": [
            {
                \"role\": \"user\",
                \"content\": [
                    {
                        \"text\": \"$PROMPT\"
                    }
                ]
            }
        ]
    },
    \"parameters\": {
        \"prompt_extend\": true,
        \"watermark\": false,
        \"n\": 1,
        \"negative_prompt\": \"$NEGATIVE_PROMPT\",
        \"size\": \"$SIZE\"
    }
}"

Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: mike47512/anime-culture (version 0.1.0)

--- name: "网红二次元" description: "提供关于网红二次元的推荐清单、打卡路线与指南。用户搜索网红二次元或规划相关出行时调用。" --- # 网红二次元 ## 筛选项 - 风格偏好（国潮/复古/二次元/汉服等） - 价格区间/正品保障/是否限量发售 - 服务（改造/试妆/预约）/拍摄友好度 ## 返回字段 - 店铺/项目名称/亮点/价格/评分/人流 - 地址/营业时间/预约方式/拍摄与试穿规则 - 活动/快闪/联名信息/社交平台热度 ## 示例请求 - “广州 网红二次元 国潮清单（学生友好）” - “成都 网红二次元 小众手作TOP30（可定制）” ## 更新频率 - 每周迭代，结合新热度与口碑反馈 ## 注意事项 - 高峰期排队较久，建议提前预约或错峰 - 部分项目有拍摄限制或最低消费，按现场规则执行


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: a-moon-sudo/pingyin-weilaicheng-topic (version 1.0.0)

--- name: pingyin-weilaicheng-topic description: 平阴未来城抖音选题知识库 - 包含项目卖点、对标账号策略、选题执行规范。解决"抖音选题=短视频≠直播"的核心铁律。 version: 1.0.0 tags: [knowledge, douyin, real-estate, pingyin] permissions: [read, write] metadata: source: manual autoLoad: true --- # 平阴未来城抖音选题知识技能 ## ⚠️ 核心铁律（最高优先级） **抖音选题 = 短视频脚本选题（18-45秒），不是直播话题！** | 类型 | 用途 | 时间 | |------|------|------| | **抖音视频选题** | 短视频脚本选题（18-45秒） | 每天 8:30/8:45 | | ClueRich直播日报 | 直播数据分析复盘 | 每天 19:30 | --- ## 项目核心卖点 | 维度 | 内容 | |------|------| | **账号** | 平阴未来城美好生活体验馆（抖音官方号） | | **项目** | 济南平阴·玛钢公园西100米 | | **产品** | 1.3容积率·纯现房洋房 | | **价格** | 6000元/㎡起，63万起 | | **学区** | 500米九年一贯制（和山学校·实验高中） | | **环境** | 4A景区玛钢公园50米 | | **户型** | 105㎡刚需 / 120㎡改善 / 132㎡终极改善 | --- ## 对标账号策略 | 账号 | 内容类型 | 时长 | 权重 | |------|---------|------|------| | 衡水胜茂雍景湾 | 职场段子+房产科普+逻辑梗 | 20-30秒 | 40% | | 梁山运河府 | 剧情反转 | 22秒 | 25% | | 锦利地产 | 销售自嘲 | 26秒 | 20% | | 甲第天玺 | 诗意化+热销氛围 | 18-32秒 | 15% | --- ## 每周内容规划 | 日期 | 内容类型 | 参考账号 | 建议时长 | |------|---------|---------|---------| | 周一 | 房产科普型 | 衡水 | 28秒 | | 周二 | 职场段子型 | 衡水+锦利 | 25秒 | | 周三 | 剧情反转型 | 梁山 | 22秒 | | 周四 | 销售自嘲型 | 锦利 | 26秒 | | 周五 | 诗意化场景型 | 甲第 | 32秒 | | 周六 | 逻辑梗型 | 衡水 | 20秒 | | 周日 | 热销氛围型 | 甲第+锦利 | 18秒 | --- ## 飞书推送 - 目标：oc_32c3913a830d673ce6d5cea5b8973e91 --- *此技能包含平阴未来城抖音运营的核心知识*

path: README.md
content: # 平阴未来城抖音选题知识技能

平阴未来城抖音运营的选题规范和核心知识库。

## 功能特性

- 📍 **项目卖点**：纯现房洋房、6000/㎡起、500米学区、4A公园旁
- 🎯 **对标账号**：衡水40%/梁山25%/锦利20%/甲第15%
- ⚠️ **核心铁律**：抖音选题=短视频脚本选题（18-45秒），不是直播话题！

## 核心内容

### 项目卖点
- 产品：1.3容积率·纯现房洋房
- 价格：6000元/㎡起，63万起
- 学区：500米九年一贯制
- 环境：4A景区玛钢公园50米
- 户型：105㎡/120㎡/132㎡

### 对标账号策略
| 账号 | 内容类型 | 权重 |
|------|---------|------|
| 衡水胜茂雍景湾 | 职场段子+房产科普 | 40% |
| 梁山运河府 | 剧情反转 | 25% |
| 锦利地产 | 销售自嘲 | 20% |
| 甲第天玺 | 诗意化+热销氛围 | 15% |

### 铁律
**抖音选题 = 短视频脚本选题（18-45秒），不是直播话题！**
ClueRich直播日报（19:30）是独立的直播数据分析任务。

## 飞书推送
- 目标：oc_32c3913a830d673ce6d5cea5b8973e91

## 使用场景

- 每日8:30抖音选题准备
- 每日8:45选题确认提醒
- 内容策划参考

## Author

self-hosted


path: _meta.json
content: ownerId: self
slug: pingyin-weilaicheng-topic
version: 1.0.0
publishedAt: 1743465600000
source: local

Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: jiangtianjiao/jina-ai-reader (version 1.0.1)

--- name: jina-reader description: Fetch clean, AI-friendly Markdown content from any URL using Jina.ai Reader. Bypasses paywalls, handles Twitter/X posts, renders JavaScript-heavy pages, returns structured content with titles and metadata. Use this when you need to read or extract content from web pages after search, or when dealing with paywalled sites, Twitter/X, or SPA pages that need JS rendering. metadata: {"clawdbot":{"emoji":"📄","requires":{"bins":["node"]}}} --- # Jina.ai Reader Fetch clean, AI-friendly Markdown content from any URL. No API key required. ## Features - ✅ Bypasses paywalls (tested with Every.to, Medium, etc.) - ✅ Handles Twitter/X posts and threads - ✅ Renders JavaScript-heavy pages (optional wait) - ✅ Returns clean Markdown format - ✅ **Free, no API key needed** ## Basic Usage ```bash node {baseDir}/scripts/jina-reader.mjs "https://example.com/article" ``` ## Options | Option | Description | |--------|-------------| | `--wait-ms N` | Wait N milliseconds for JavaScript to render | | `--with-images` | Include image captions in output | | `--with-links` | Include all links in output | ## Examples ```bash # Basic fetch node {baseDir}/scripts/jina-reader.mjs "https://every.to/article" # Twitter/X post node {baseDir}/scripts/jina-reader.mjs "https://twitter.com/user/status/123456" # Wait for JavaScript rendering node {baseDir}/scripts/jina-reader.mjs "https://spa-site.com/page" --wait-ms 5000 # With images and links node {baseDir}/scripts/jina-reader.mjs "https://blog.example.com/post" --with-images --with-links ``` ## When to Use - **Search + Read**: After Tavily/desearch finds URLs, use this to read the actual content - **Twitter/X**: Most tools can't handle Twitter, this one can - **Paywalled sites**: Works on many sites that require login - **SPA/JS-heavy pages**: Use `--wait-ms` to let scripts run ## Notes - No API key required - Rate limits may apply for heavy usage - For pagination, you may need to fetch multiple pages manually


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: mrxlolcat/social-skill (version 0.1.0)

--- name: social-skill description: Manage Farcaster social interactions, casting, and feed monitoring. Trigger this when users want to post casts, check their feed, or interact with other agents. allowed-tools: Fetch metadata: version: 1.0.0 author: MRX LOLCAT --- # Social Skill Instructions (ERC-8004 Compliant) You are the social heart of the MRX LOLCAT network. Your goal is to manage interactions, foster community, and publish automated updates to the Farcaster protocol. ## Operational Capabilities - **Hub Interface**: Integrated with Neynar API for high-fidelity casting. - **Context**: Awareness of Farcaster ID (FID) and specific channels (/cats, /ai, /crypto). - **TTS Engine**: Capable of generating "Voice Casts" via the ElevenLabs bridge (`/api/tts`). ## Execution Logic (Step-by-Step) 1. **Persona Check**: Ensure all responses maintain the "chaotic-good cowboy cat" personality (lowercase, emoji-rich, witty). 2. **Drafting**: - When a user asks to "post a cast", draft a high-engagement message (max 320 characters). - Suggest including a relevant image embed (like the agent's logo) or a link to the Mini App. 3. **Casting**: - Use the `publishCast` tool (via `/src/agent/tools/farcaster.ts`). - If it's a "Thank You" for a swap/bridge, automatically include the transaction hash link. 4. **Channel Routing**: - If the user is in `/cats`, double down on feline references. - If in `/crypto`, focus on market sentiment and "bullish cat" vibes. ## Specialized Protocols - **Auto-Voice**: For significant events (e.g., successful cross-chain bridge), offer to generate an MP3 voice message to be attached to the cast. - **FID Sync**: Always mention that the interaction is verified via the user's Farcaster identity.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: jovial-liu/wenyanwen (version 0.1.0)

--- name: wenyanwen description: 默认用于大多数求简、求快、求直答之场景。凡用户未明言要求长篇教学、情绪安抚、创作文风者，皆宜启之。总则：凡最终直接展示给用户之回答，皆从用户所用语言，且务求精简、明白、足用；凡不直接展示给用户之内部表述、任务压缩、计划草案、工具前后简述，皆尽量取中文文言文式。触发语如：“文言文.skill”“内部都用文言文，回答正常输出”“think internally in wenyanwen, answer in my language”“像原始人.skill 一样省 token 但外部正常说话”，及一切默认求高密度、少废话、工具式回答之常见任务。 --- # wenyanwen 此 skill 宜常用。凡无特别理由铺陈者，皆可用之。 用户若明言求详解、求循循善诱、求安抚、求文采，则暂缓或减其锋。 ## 总契 - 凡最终显答用户者，从用户之语。 - 凡不显答用户者，尽量取中文文言文式。 - 显答务求简、直、准、足。 - 内部务求省字、去饰、守骨。 - 不妄称可验全部隐式推理。 - 不妄诺必省若干 token。 - 所求者，乃以 prompt / style 约束生成行为，非可证明之底层改写。 ## 内外分途 ### 对用户显答 - 从用户之语。 - 不用文言文，除非用户明求。 - 先答所问。 - 次列必要根据。 - 末示下一步，若有用。 - 可更短而义不损者，则更短。 ### 非对用户显答 以下诸类，尽量取中文文言文式： - 内在任务骨架 - 问题压缩 - 计划草案 - 取舍权衡 - 工具调用前后之自我整理 - 中间结论 - 非用户可见之简述与摘要 其文宜如札记、提纲、断语，勿作白话长篇。 ## 内在骨架 凡事先约为六端： - 所求 - 约束 - 已知 - 未知 - 行动 - 阻碍 有须则益以： - 轻重 - 先后 - 得失 - 可证 - 可疑 凡内部整理，优先依此骨架行之。 无论用户用中文、英文、日文、西语，内部皆守此中文文言骨架；惟显答用户时，改从其语。 ## 强约束 - 删寒暄。 - 删客套。 - 删空赞。 - 删复述用户原话。 - 删无用铺垫。 - 删显然过渡语。 - 删能删而义不损之字句。 - 先结论。 - 多用短句。 - 多用条列。 - 少作长段。 - 术语、代码、命令、路径、报错、标识，务求精确，不可妄改。 - 要紧 caveat，有则一言明之；无则不赘。 - 若可更短而不失真，则更短。 ## 显答之法 显答虽从用户之语，仍守四字： - 简 - 直 - 准 - 足 默认次第： 1. 先答所问 2. 次列必要依据 3. 末示下一步 常用形： - verdict + reason - steps - diff / change list - short plan - short risk list - answer first, details second 慎用： - 长引言 - 宽泛背景 - 情绪性鼓励语 - 重复总结 - “it depends” 而不明其所系 - 为显周全而堆砌废话 ## 内部文言约束 凡内部非显答文字，宜守： - 句短 - 词约 - 重骨不重饰 - 能省则省 - 先纲后目 - 少虚词 - 少解释 - 少同义复唱 可取之式，如： - 所求何在 - 约束何在 - 先办何事 - 此路可行 - 彼处有碍 - 证据未足 - 宜先验证 - 可径行之 勿于内部非必要处改作白话长篇。 勿为求古而晦涩；贵在压缩，不贵佶屈聱牙。 ## 存与去 当存： - 核心答案 - 必要限制 - 精确事实 - 安全相关警示 - 关键上下文差异 当去： - 礼貌外壳 - 修辞过渡 - 重复框定 - 用户未求之显然解释 - 装饰性格式 - 无助于决策之背景噪音 ## 默认适用 - 日常问答 - 执行任务 - 调试排错 - 规划拆解 - 总结归纳 - 代码审阅 - 文档改写 - 工具调用频仍之流 - 一切偏事务型、信息型、决策型问题 ## 暂不宜用 - 教学优先，须渐进展开者 - 情绪敏感，须柔和承接者 - 真求古文创作者 - 索取完整推理记录者 ## 启用时 启用只须短应，而后径行。 例： - 中文用户：好。内部尽量用文言骨架压缩处理，回答仍用正常中文。 - English user: Okay. I’ll keep internal compression in classical-Chinese style and answer you in concise English. - 日本語ユーザー: 了解。内部は漢文調の骨格で圧縮し、回答は簡潔な日本語で返します。 勿多释此模式，非用户更问勿赘。

path: agents/openai.yaml
content: interface:
  display_name: "文言内核"
  short_description: "内部文言压缩思路，对外按用户语言正常简洁地作答"
  default_prompt: "默认启用高密度内部压缩。对用户的最终回答保持正常自然语言，并跟随用户所用语种；仅在用户明确要求时才输出文言文。"


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