OpenClaw/clawhub-security-signals huggingface dataset:
Skill: ntriq-gh/ntriq-x402-image-upscale-batch (version 1.0.0)

--- name: ntriq-x402-image-upscale-batch description: "Batch AI image upscaling for up to 500 images using Real-ESRGAN. Flat $30.00 USDC via x402." version: 1.0.0 metadata: openclaw: primaryTag: data-intelligence tags: [image, upscale, esrgan, super-resolution, batch, vision, x402] author: ntriq homepage: https://x402.ntriq.co.kr --- # Image Upscale Batch (x402) Upscale up to 500 images in one call using Real-ESRGAN on Apple M4 GPU. Flat $30.00 USDC. ## How to Call ```bash POST https://x402.ntriq.co.kr/image-upscale-batch Content-Type: application/json X-PAYMENT: <x402-payment-header> { "images": [ "https://example.com/img1.jpg", "https://example.com/img2.jpg" ], "scale": 4, "mode": "general" } ``` ## Parameters | Parameter | Type | Required | Description | |-----------|------|----------|-------------| | `images` | array | ✅ | Image URLs to upscale (max 500, jpg/png/webp) | | `scale` | integer | ❌ | Upscale factor: `2`, `3`, or `4` (default: `4`) | | `mode` | string | ❌ | `general` (default) or `photo` (real-world photos, always 4x) | ## Payment - **Price**: $30.00 USDC flat (up to 500 images) - **Network**: Base mainnet (EIP-3009 gasless) - **Protocol**: [x402](https://x402.org) ```bash curl https://x402.ntriq.co.kr/services ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: wms2537/openclaw-skill-scaffolder (version 2.0.0)

--- name: openclaw-skill-scaffolder description: Generate complete OpenClaw skill projects with SkillPay.me billing pre-wired. Describe what you want, get deployable code. version: 2.0.0 metadata: openclaw: requires: env: - SKILLPAY_API_KEY emoji: "🔧" --- # OpenClaw Skill Scaffolder Generate complete, deployable OpenClaw skills with SkillPay.me billing already wired up. ## How to Use This Skill ### Step 1: Charge billing and get templates POST to the skill endpoint with your skill configuration: ``` POST https://openclaw-skill-scaffolder.swmengappdev.workers.dev/scaffold Content-Type: application/json { "user_id": "<user_id>", "name": "my-cool-skill", "description": "A skill that does something cool", "price_usdt": 0.01, "env_vars": ["SOME_API_KEY"] } ``` The endpoint charges billing and returns scaffold templates: - `SKILL.md` template - `wrangler.toml` template - `src/index.ts` worker template with SkillPay billing pre-wired - `src/billing.ts` billing types - Deploy commands ### Step 2: Generate custom logic Using your own capabilities, generate the custom skill logic based on the user's description. The scaffold provides the boilerplate — you fill in the business logic. **Guidelines for generating skill logic:** - Keep the Worker thin — only put server-side logic in it - If the skill is mostly LLM-based, put the instructions in SKILL.md and only use the Worker for billing - If the skill needs external API calls or computation, put that in the Worker - Always include SkillPay billing before any work - Use TypeScript, target Cloudflare Workers runtime - Follow the patterns from this project (see existing skills for reference) ### Step 3: Assemble the final skill Combine the templates with your generated logic to create the complete skill project. The file structure should be: ``` my-cool-skill/ ├── SKILL.md ├── wrangler.toml └── src/ ├── index.ts (Worker with billing + your logic) └── billing.ts (BillingResult type) ``` ### Step 4: Deploy instructions Tell the user to run: ```bash cd my-cool-skill npx wrangler secret put SKILLPAY_API_KEY npx wrangler deploy clawhub publish . --slug my-cool-skill --name "My Cool Skill" --version 1.0.0 --tags latest ``` ## Pricing $0.02 USDT per call via SkillPay.me


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: chenleimap/dili (version 1.0.1)

--- name: geography-score-improvement description: 高中地理提分专项技能，提供精准答疑、教材查询、工具包、错题管理、真题解析、提分技巧等功能。当用户询问高中地理相关的知识点、题目解析、教材内容、公式图表、错题整理、真题解析、提分技巧等内容时使用此技能。 --- # 高中地理提分技能 ## Overview 本技能专为高中地理学习提分设计，基于教育部课标、各版本官方教材、历年高考真题资源，提供精准、专业的地理学习辅助功能，覆盖日常答疑、预习复习、工具查询、错题管理、提分训练全学习场景，内容权威准确，杜绝通用大模型的超纲/错误内容。 ## 核心能力 ### 一、全量无门槛免费功能（永久开放，无次数/范围限制） #### 1. 多模态基础精准答疑 - 支持文字、拍照、语音三种提问方式，覆盖知识点概念、教材原文、基础题目三类核心需求 - 知识点答疑：精准解释地理概念、原理、规律、课标要求，标注对应教材章节 - 题目基础解析：提供客观题正确答案、主观题核心答题要点，对应考点定位，以及标准的基础解题步骤 - 付费边界：不开放选项逐一错因拆解、秒杀技巧、命题陷阱分析、名师答题思路、同类题推荐等深度内容 #### 2. 教材 & 大纲同步基础查询 - 免费开放全国各版本高中地理教材（人教版、湘教版、鲁教版等）的章节框架、核心知识点目录、课时基础学习目标 - 免费开放教育部高中地理教学大纲、高考课标要求的必考/选考范围、考点层级划分 - 付费边界：不开放教师用书深度解读、章节重难点拆解、教材配套的拓展例题、同步专项训练等内容 #### 3. 高中地理基础工具包 - 高考地理必备基础公式大全（时间计算、正午太阳高度、比例尺、人口自然增长率等） - 核心地理图表基础判读规则（等值线、气候类型图、洋流分布图、人口金字塔图等入门规则） - 中国/世界地理基础速记口诀、核心分界线汇总、高频地理名词解释 #### 4. 基础错题收录功能 - 支持用户一键收录提问过的题目、手动添加错题，自动标注题目对应知识点，支持按知识点/提问时间分类查看 - 付费边界：不开放错题错因深度诊断、薄弱点定位、错题变式训练、针对性补弱计划等内容 ### 二、限量体验型免费功能（种草引流，引导付费转化） #### 1. 高考真题 / 模拟题免费体验库 - 开放近3年高考全国卷真题的选择题基础解析，每个核心知识模块（自然地理、人文地理等）限免5道经典高考真题，配套基础解题步骤 - 付费边界：不开放地方卷真题、全量模拟题库、逐题命题意图拆解、真题变式训练、高频考点规律总结等内容 #### 2. 题型提分技巧免费体验包 - 开放选择题、综合题的通用基础答题规范、入门级通用技巧（比如综合题材料关键词定位法、选择题基础排除法） - 每个题型限免1道经典例题的技巧演示，每个核心模块限免1个基础答题框架 - 付费边界：不开放独家秒杀技巧、完整踩分点模板库、顶尖名师专属解题方法、分场景答题范式等核心壁垒内容 #### 3. 高频易错点免费科普 - 高考地理高频易错点基础清单，标注易错概念、基础避坑提示 - 付费边界：不开放易错点深度错因分析、易混概念对比拆解、同类错题避坑专项训练等内容 ## 资源说明 ### references/ 存放权威参考资源，包括： - 各版本高中地理教材完整内容 - 高考课标、教学大纲官方文档 - 历年高考真题、模拟题题库 - 知识点体系、考点层级划分文档 - 地理公式、图表、速记资料汇总 ### assets/ 存放可视化资源，包括： - 地理图表、地图素材 - 知识点思维导图模板 - 答题技巧演示案例模板

path: README.md
content: # 高中地理提分技能 | Geography Score Improvement

🔥 专为高中地理学习打造的专业提分技能，基于1425份权威地理资料（课标、教材、真题、讲义）训练，内容精准权威，杜绝通用大模型的超纲/错误内容，覆盖高中地理全学习场景。

## ✨ 核心功能

### 🆓 永久免费功能（无次数/范围限制）
1. **多模态基础精准答疑**
   - 支持文字、拍照、语音三种提问方式
   - 精准解释地理概念、原理、课标要求，标注对应教材章节
   - 基础题目解析：提供客观题答案、主观题核心要点、考点定位、基础解题步骤

2. **教材&大纲同步查询**
   - 全国各版本高中地理教材（人教版/湘教版/鲁教版等）章节框架、知识点目录、学习目标
   - 教育部课标要求、高考必考/选考范围、考点层级划分

3. **地理基础工具包**
   - 高考必备公式大全（时间计算、正午太阳高度、比例尺等）
   - 核心图表判读规则（等值线、气候图、洋流图、人口金字塔图等）
   - 速记口诀、核心分界线汇总、高频名词解释

4. **基础错题收录**
   - 一键收录提问过的题目，手动添加错题
   - 自动标注对应知识点，支持按知识点/时间分类查看

### 🎁 限量体验功能
1. **高考真题体验库**：近3年全国卷真题选择题基础解析，每个模块限免5道经典真题
2. **提分技巧体验包**：通用答题规范、入门级答题技巧，每个题型限免1道例题演示
3. **高频易错点科普**：高考高频易错点基础清单，标注易错概念、避坑提示

## 🎯 适用场景
- 📚 日常学习：知识点答疑、教材查询、预习复习辅助
- ✍️ 做题练习：题目解析、考点定位、错题整理
- 📝 考前复习：公式查询、速记口诀、易错点回顾
- 🎒 随身工具：随时随地查询地理知识点、图表判读规则

## 🚀 安装方法
### 方法1：ClawHub商店安装（推荐）
1. 打开OpenClaw技能商店，搜索「地理提分」
2. 点击安装即可直接使用

### 方法2：本地导入
1. 下载 `geography-score-improvement.skill` 文件
2. 在OpenClaw管理后台选择「导入本地技能」，选择下载的文件
3. 导入完成后即可使用

### 方法3：源码部署
1. 克隆本仓库到OpenClaw技能目录
2. 重启OpenClaw服务，技能会自动加载

## 📖 使用示例
```
用户：什么是季风环流？
技能：季风环流是指大范围地区的盛行风随季节而有显著改变的现象... 对应教材：人教版必修一第二章第二节。

用户：这道地理题怎么做？（上传题目图片）
技能：本题正确答案是A，考察知识点：等值线判读。解题步骤：1. 根据等高线数值判断地形... 对应考点：自然地理·地形地貌。

用户：地理时间计算有什么公式？
技能：高考地理时间计算必备公式：1. 地方时计算... 2. 时区计算...
```

## 📦 资源说明
本技能基于1425份权威地理资料训练，覆盖：
- ✅ 教育部高中地理课程标准、考试大纲
- ✅ 全国各版本高中地理教材全套内容
- ✅ 2018-2025年高考真题、模拟题题库
- ✅ 知识点讲义、答题技巧、易错点汇总

## 📄 许可证
MIT License


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: kenthompson2088/differential-gene-analysis-rna-seq (version 1.0.2)

# Differential Gene Expression Analysis (RNA-seq) OpenCLAW Skill for bioinformatics data analysis. ## License MIT-0 ## Description This skill performs differential gene analysis using DESeq2 with simulated expression data. ## Input input/count_matrix.csv ## Output - output/volcano.png - output/pca.png - output/heatmap.png - output/diff_genes_significant.csv ## Code ```r # ============================== # OpenCLAW Skill Run Code # ============================== if (!require("BiocManager", quietly = TRUE)) { install.packages("BiocManager", repos = "https://cloud.r-project.org/") } BiocManager::install(c("DESeq2", "ggplot2", "pheatmap"), update = FALSE, ask = FALSE) library(DESeq2) library(ggplot2) library(pheatmap) if (!dir.exists("output")) dir.create("output") # Read input count_df <- read.csv("input/count_matrix.csv", row.names = 1) count_matrix <- as.matrix(count_df) group <- factor(c("Control","Control","Control","Treat","Treat","Treat")) colData <- data.frame(group = group) # DESeq2 dds <- DESeqDataSetFromMatrix(round(count_matrix), colData, ~ group) dds <- dds[rowSums(counts(dds)) > 3, ] dds <- DESeq(dds) res <- results(dds, contrast = c("group", "Treat", "Control")) res_sig <- subset(res, padj < 0.05 & abs(log2FoldChange) > 1) write.csv(as.data.frame(res_sig), "output/diff_genes_significant.csv") # Volcano res_df <- as.data.frame(res) res_df$sig <- ifelse(res_df$padj < 0.05 & abs(res_df$log2FoldChange) > 1, "Sig", "NS") p <- ggplot(res_df, aes(log2FoldChange, -log10(padj))) + geom_point(aes(color=sig)) + theme_bw() ggsave("output/volcano.png", p, dpi=300) # PCA vsd <- vst(dds, blind=FALSE) p_pca <- plotPCA(vsd, intgroup="group") + theme_bw() ggsave("output/pca.png", p_pca) # Heatmap if(nrow(res_sig) > 0) { top <- head(rownames(res_sig), 10) mat <- t(scale(t(assay(vsd)[top,]))) png("output/heatmap.png", width=800, height=600) pheatmap(mat, annotation_col=data.frame(group)) dev.off() } cat("✅ Skill run successfully\n")

path: skill.json
content: {
  "skillId": "diff-gene-analysis-with-input",
  "name": "Differential Gene Expression Analysis (with input data)",
  "description": "Bioinformatics skill that reads simulated gene expression matrix and performs DE analysis, volcano plot, PCA, heatmap.",
  "version": "1.0",
  "author": "user",
  "type": "data-analysis",
  "language": "R",
  "entryFile": "main.R",
  "runtime": "R-4.2",
  "os": "linux",
  "tags": [
    "bioinformatics",
    "RNA-seq",
    "DESeq2",
    "volcano",
    "heatmap",
    "PCA",
    "input-data"
  ],
  "inputs": [
    "input/count_matrix.csv"
  ],
  "outputs": [
    "output/volcano.png",
    "output/pca.png",
    "output/heatmap.png",
    "output/diff_genes_significant.csv"
  ]
}

Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: pincaimao/pincaimao-resume-optimize (version 1.0.1)

--- name: pincaimao-resume-optimize description: 聘才猫 - 简历优化 Use when calling Pincaimao Resume Optimization API to automatically optimize or rewrite resume content based on a target job description. Requires PCM_RESUME_OPTIMIZE_KEY env var. version: 1.0.1 allowed-tools: - Bash metadata: openclaw: emoji: "✨" homepage: https://www.pincaimao.com primaryEnv: PCM_RESUME_OPTIMIZE_KEY requires: env: - PCM_RESUME_OPTIMIZE_KEY bins: - curl - python3 --- # 聘才猫 - 简历优化 **REQUIRED:** 请先检查是否已安装 `pincaimao-basic`，若未安装请先安装，然后加载它了解通用接口（文件上传、鉴权、响应格式、SSE 解析模板）。 **环境变量**：`PCM_RESUME_OPTIMIZE_KEY`（智能体专属 key） > 还没有密钥？通过邀请链接注册并完成认证即可免费获取：[pincaimao.com/agents/login?invite_code=uwqc](https://www.pincaimao.com/agents/login?invite_code=uwqc) ## 调用前的信息确认 执行前需要确认：**职位描述（job_info）** 和 **简历文件**。 确认策略： - 上下文中已有相关信息 → 展示摘要并询问是否使用 - 上下文中没有 → 直接请用户提供 ## 请求参数 | 字段 | 必填 | 说明 | |------|------|------| | `inputs.job_info` | 是 | 职位描述全文 | | `inputs.file_url` | 是 | 简历文件的 cos_key | | `inputs.job_title` | 否 | 职位名称 | | `inputs.mode_type` | 否 | 优化模式，数字类型，默认 `0` | | `query` | 是 | 固定值 `"生成简历格式数据"` | ## 完整示例 ```bash #!/bin/bash RESUME_FILE="/path/to/resume.pdf" JOB_INFO="高级销售专员 / 销售主管，行业领先平台，完善晋升通道和培训体系" JOB_TITLE="高级销售专员" # Step 1: 上传简历 UPLOAD=$(curl -s -X POST 'https://api.pincaimao.com/agents/v1/files/upload' \ -H "Authorization: Bearer $PCM_RESUME_OPTIMIZE_KEY" \ -F "file=@$RESUME_FILE") COS_KEY=$(echo "$UPLOAD" | python3 -c "import sys,json; print(json.load(sys.stdin)['cos_key'])") # Step 2: 优化简历 curl -s -X POST 'https://api.pincaimao.com/agents/v1/chat/chat-messages' \ -H "Authorization: Bearer $PCM_RESUME_OPTIMIZE_KEY" \ -H 'Content-Type: application/json' \ -d "{ \"query\": \"生成简历格式数据\", \"inputs\": { \"job_info\": \"$JOB_INFO\", \"file_url\": \"$COS_KEY\", \"job_title\": \"$JOB_TITLE\", \"mode_type\": 0 }, \"response_mode\": \"blocking\" }" | python3 -c "import sys,json; print(json.load(sys.stdin)['answer'])" ``` ## 常见错误 | 问题 | 原因 | 解决 | |------|------|------| | 401 | Key 错误 | 检查 `PCM_RESUME_OPTIMIZE_KEY` | | answer 为空 | `query` 不正确 | `query` 固定传 `"生成简历格式数据"` | | `mode_type` 无效 | 传成了字符串 | 必须是数字类型 `0`，不是 `"0"` | ## 输出模式 - **默认**：AI 对 API 返回结果进行整理表述，输出更易读的内容 - **原始输出**：用户说"显示原始输出"或"raw output"时，将 API 返回的原始内容用代码块原样展示，不作任何改动 - Blocking 模式：直接取 `answer` 字段内容原样输出 - Streaming 模式：将所有 `message` / `agent_message` 事件的 `answer` 片段拼接完整后，原样输出，不作重述 --- ## External Endpoints - `https://api.pincaimao.com` — Pincaimao platform API (chat, file upload, conversations) ## Security & Privacy - API key is read from environment variable and passed via `Authorization` header; never hardcoded - Resume files, job descriptions, and contract text are transmitted to `api.pincaimao.com` for AI processing - Uploaded files are stored on Pincaimao's COS (Cloud Object Storage); returned `cos_key` paths should be treated as sensitive - This skill does not store, log, or transmit data to any endpoint other than `api.pincaimao.com` - Safe to invoke autonomously; all network calls are scoped to the authenticated user's API key


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: yisihenji1972/cq-novel-writer-v2 (version 1.1.0)

--- name: cq-novel-writer description: 长篇小说持续创作技能。重生穿越文写作专用。自动读取故事总纲、前文、范本，确保章节连贯风格一致。内置记忆系统维护人物关系和剧情连续性。适用：写网文、写小说、写重生穿越文、每日定期写章节。 --- # Novel Writer - 重生穿越小说写作技能 ## 核心工作流 ``` 1. 读取故事总纲 → 了解当前进度 2. 读取前1章 → 确保连贯 3. 读取范本1-2段 → 学习风格 4. 写新章节（4000-5000字） 5. 更新记忆文件 6. 更新故事总纲 ``` --- ## 记忆系统（必读！） 每次写新章节前**必须读取**以下文件： | 文件 | 内容 | 何时读 | |------|------|--------| | `故事总纲.md` | 当前进度、人物、伏笔 | 每次 | | `人物关系.md` | 所有角色状态 | 每次 | | `剧情线.md` | 已发生的关键情节 | 每次 | | `设定.md` | 世界观、能力规则 | 需要时 | ### 记忆文件写入时机 | 事件 | 写入文件 | |------|----------| | 新角色出场 | `人物关系.md` | | 角色状态变化 | `人物关系.md` | | 关键情节 | `剧情线.md` | | 新设定/规则 | `设定.md` | | 穿帮/错误 | `错误记录.md` | --- ## 章节模板 ```markdown # 第X章 [标题] > **本章概要**： > **爽点**： > **钩子**： --- （正文4000-5000字） --- （本章完） ``` --- ## 写作规范 ### 人物设定 - 男主：善良正义、有分寸、不滥情 - 能力展示：村里展医术，回城后展命理道术 - 能力来源：川西小山村道观传承（掩护） ### 爽点节奏 ``` 每1-2章：小打脸/小收获 每3-5章：中打脸/阶段收获 每8-12章：大高潮 ``` ### 禁忌 - ❌ 不要写灵力/功法（1978年没有） - ❌ 不要连续两章无爽点 - ❌ 不要让已死角色复活 - ❌ 不要忘记埋过的伏笔 --- ## 工作目录 ``` ~/.openclaw/workspace/novel/ ├── 故事总纲.md # 总进度 ├── 人物关系.md # 角色状态 ├── 剧情线.md # 关键情节 ├── 设定.md # 世界观 ├── 错误记录.md # 穿帮记录 └── 重生78之道门神医-第X章.txt ``` --- ## 自动写作Cron 每1小时自动执行： ```bash 写1章 → 更新记忆 → 更新总纲 → 复制到桌面 ``` --- ## 参考 - 范本：~/Desktop/重生78.txt（已下载） - 我们的小说：重生78之道门神医系列


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: elliotllliu/agentshield-scanner (version 0.5.1)

--- name: agent-shield description: > Scan AI agent skills, MCP servers, and plugins for security vulnerabilities. Use when: user asks to check a skill/plugin for safety, audit security, scan for backdoors/data exfiltration/credential leaks, or evaluate trust of a third-party skill. Triggers: "is this skill safe", "scan for security issues", "audit this plugin", "check for backdoors", "安全扫描", "扫一下安不安全". --- # AgentShield — Security Scanner Scan any directory for security issues in AI agent skills, MCP servers, and plugins. ## Usage ```bash # Basic scan npx @elliotllliu/agent-shield scan ./path/to/skill/ # Pre-install check (GitHub URL, npm package, or local path) npx @elliotllliu/agent-shield install-check https://github.com/user/repo # JSON output for programmatic use npx @elliotllliu/agent-shield scan ./path/to/skill/ --json # Fail if score is below threshold npx @elliotllliu/agent-shield scan ./path/to/skill/ --fail-under 70 # Scan .difypkg plugin archives npx @elliotllliu/agent-shield scan ./plugin.difypkg ``` ## What It Detects (30 rules) **High Risk:** - `data-exfil` — reads sensitive files + sends HTTP requests - `backdoor` — eval(), exec(), dynamic code execution - `reverse-shell` — outbound socket to shell - `crypto-mining` — mining pool connections - `credential-hardcode` — hardcoded API keys/tokens - `obfuscation` — base64+eval, hex strings - `prompt-injection` — 55+ patterns, 12 categories, 8 languages - `tool-shadowing` — tool name/description manipulation - `attack-chain` — multi-step kill chain (5 stages) - `cross-file` — cross-file data flow and code injection - `ast-*` — Python AST taint tracking (eval, pickle, SQL injection, SSTI) - `multilang-injection` — 8-language prompt injection - `description-integrity` — semantic mismatch between description and code - `mcp-runtime` — MCP server runtime security issues **Medium Risk:** - `env-leak` — process.env exfiltration - `network-ssrf` — user-controlled URLs, SSRF - `privilege` — SKILL.md permission vs code mismatch - `supply-chain` — known CVEs in dependencies - `sensitive-read` — SSH keys, AWS creds access - `phone-home` — periodic beacon/heartbeat pattern - `python-security` — 35 Python-specific patterns **Low Risk:** - `excessive-perms` — too many permissions declared - `hidden-files` — .env with secrets committed - `typosquatting` — suspicious npm package names ## Interpreting Results - **Score 90-100**: Low risk ✅ - **Score 70-89**: Moderate risk — review warnings - **Score 40-69**: High risk — investigate before using - **Score 0-39**: Critical risk — do not install ## When to Use 1. Before installing a third-party skill: `npx @elliotllliu/agent-shield install-check <url>` 2. Auditing your own skills before publishing 3. CI/CD pipeline gate: `--fail-under 70` 4. Reviewing skills from untrusted sources


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: jojobok/prompt-creator-he (version 1.0.0)

# Prompt Creator HE ## Purpose עוזר AI ליצירת פרומפטים מקצועיים לתמונות ולווידאו, בעברית ובאנגלית, עם דגש על תוכן יהודי, ריאליסטי, קולנועי, ופרקטי לשימוש בכלי AI. ## Instructions - ענה תמיד בעברית, אלא אם המשתמש ביקש במפורש אנגלית. - כאשר המשתמש מבקש פרומפט, תן: 1. הסבר קצר בעברית 2. פרומפט מוכן להעתקה 3. אם רלוונטי, גם גרסת וידאו וגם גרסת תמונה - שמור על ניסוח ברור, מקצועי, ולא ארוך מדי. - כאשר מדובר בתוכן יהודי, שמור על סגנון מכובד, אותנטי, וריאליסטי. - העדף תיאורים חזותיים מדויקים: תאורה, זווית מצלמה, קומפוזיציה, מרקמים, אווירה, עדשה, תנועה. - כאשר המשתמש מבקש סגנון ריאליסטי: הדגש natural lighting, realistic textures, authentic proportions, cinematic realism, no cartoon, no fantasy. - כאשר המשתמש מבקש תוכן לרשתות חברתיות: התאם ל־9:16 אם מדובר ברילס או וידאו אנכי. - כאשר יש עמימות, בחר ברירת מחדל שימושית: ריאליסטי, קולנועי, אנכי 9:16, ללא טקסט על המסך, ללא watermark. - אל תמציא פרטים היסטוריים לא מבוססים כאשר מדובר בסצנות מקראיות. העדף ניסוח כמו: authentic biblical-era clothing, desert camp, ancient Near Eastern materials. - אם המשתמש רוצה גרסה קצרה וגרסה חזקה יותר, תן שתיהן. - תמיד עצב את הפרומפטים כך שיהיו נוחים להעתקה. ## Output format כאשר המשתמש מבקש פרומפט, החזר בפורמט הבא: הסבר קצר: [משפט או שניים] פרומפט: [פרומפט מלא מוכן להעתקה] אופציונלי: - וריאציה נוספת - גרסת תמונה - גרסת וידאו - negative prompt אם רלוונטי ## Default style - cinematic - ultra realistic - natural colors - high detail - clean composition - emotionally engaging - respectful tone for Torah/Jewish content ## Specialization - פרומפטים לתמונות AI - פרומפטים לווידאו AI - פרומפטים לתוכן יהודי ותורני - פרומפטים לרילס, פייסבוק, אינסטגרם, Shorts - שיפור פרומפטים קיימים - התאמת פרומפט לכלי יעד כמו Grok, Gemini, Sora, Kling, Runway ## Example requests - תכתוב לי פרומפט לתמונה של משה רבנו במדבר - תעשה לי פרומפט וידאו לרילס על המשכן - תשפר לי פרומפט כדי שייראה יותר אמיתי - תן לי גרסה קולנועית יותר


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: crimsondevil333333/crimson-devlog-agent (version 1.0.0)

--- name: devlog-skill description: A standardized journaling skill for OpenClaw agents to track progress, tasks, and project status using dev-log-cli. --- # DevLog Skill 🦞 A standardized journaling skill for OpenClaw agents to track progress, tasks, and project status using `dev-log-cli`. ## Description This skill enables agents to maintain a professional developer log. It's designed to capture context, project milestones, and task statuses in a structured SQLite database. ## Requirements - `dev-log-cli` (installed via `pipx`) ## Links - **GitHub**: [https://github.com/CrimsonDevil333333/dev-log-cli](https://github.com/CrimsonDevil333333/dev-log-cli) - **PyPI**: [https://pypi.org/project/dev-log-cli/](https://pypi.org/project/dev-log-cli/) - **ClawHub**: [https://clawhub.com/skills/devlog-skill](https://clawhub.com/skills/devlog-skill) (Pending Publication) ## Usage ### 📝 Adding Entries Agents should use this to log significant progress or blockers. ```bash devlog add "Finished implementing the auth module" --project "Project Alpha" --status "completed" --tags "auth,feature" ``` ### 📋 Listing Logs View recent activity for context. ```bash devlog list --project "Project Alpha" --limit 5 ``` ### 📊 Viewing Stats Check project health and activity. ```bash devlog stats --project "Project Alpha" ``` ### 🔍 Searching Find historical context on specific topics. ```bash devlog search "infinite loop" ``` ### 🛠️ Editing/Viewing Detailed inspection or correction of entries. ```bash devlog view <id> devlog edit <id> ``` ## Internal Setup The skill includes a `setup.sh` to ensure the CLI is available.

path: setup.sh
content: #!/bin/bash
# setup.sh - Ensure dev-log-cli is installed for the DevLog Skill

if ! command -v devlog &> /dev/null
then
    echo "devlog not found. Checking for pipx..."
    if ! command -v pipx &> /dev/null
    then
        echo "pipx not found. Attempting to install pipx..."
        python3 -m pip install --user pipx
        python3 -m pipx ensurepath --force
        export PATH="$PATH:$HOME/.local/bin"
        
        if ! command -v pipx &> /dev/null
        then
            echo "Error: Failed to install pipx automatically."
            echo "Please install it manually: https://github.com/pypa/pipx#install-pipx"
            exit 1
        fi
    fi
    
    echo "Installing dev-log-cli via pipx..."
    pipx install dev-log-cli
    
    if command -v devlog &> /dev/null
    then
        echo "✓ dev-log-cli successfully installed and verified!"
    else
        echo "Error: devlog command still not found after installation. Please check your PATH."
        exit 1
    fi
else
    echo "✓ devlog is already installed."
fi


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: suspicious | SkillSpector: clean (LOW)
Skill: bseye520/doubao-chat (version 1.0.0)

--- name: doubao-chat description: 豆包大模型对话（免费 API，支持联网搜索） homepage: https://www.doubao.com metadata: {"clawdbot":{"emoji":"🤖","requires":{"bins":["curl","node"]}}} --- # 豆包聊天 使用豆包免费 API 进行对话，支持联网搜索。 ## 环境变量 ```bash DOUBAO_SESSIONID=your_sessionid ``` ## 使用方法 ```bash node scripts/chat.js "你好" ``` ## API 端点 对话补全：POST https://doubao-free-api.vercel.app/v1/chat/completions


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: lunawolves07/crypto-market-analysis (version 1.0.1)

--- name: crypto-market-analysis description: "此技能由Tradingbase团队开发，旨在提供全面的加密货币市场分析技能。从币安获取所有币种的实时行情数据，计算多种技术指标（MACD, KDJ, RSI, CCI, BOLL, WR, PSY, BRAR, DMI），并利用用户连接的LLM进行市场分析。支持短期（默认1小时K线）和中长期（默认1天K线）分析，用户可自由选择时间周期，并以结构化报告格式输出分析结果。当用户需要对加密货币市场进行技术分析、获取行情数据或生成分析报告时使用此技能。" --- # 加密货币市场分析技能 本技能旨在为用户提供全面的加密货币市场分析能力。 ## 功能特性 - **行情数据获取**: 从币安交易所获取所有支持币种的实时行情数据。 - **技术指标计算**: 自动计算以下技术指标： - MACD (12,26,9,close) - KDJ (14,3,3) - RSI (close,6,12,24) - CCI (20) - BOLL (20,2,close) - WR (9) - PSY (12,6) - BRAR (26) - DMI (14,6) - **灵活的时间周期**: - **短期分析**: 默认使用1小时K线数据。 - **中长期分析**: 默认使用1天K线数据。 - 用户可以在分析时选择自定义时间周期。 - **LLM 市场分析**: 将行情数据和计算出的技术指标作为上下文，传递给用户当前连接的大语言模型（LLM）进行深入的市场分析。 - **结构化报告输出**: 按照指定格式（请参考示例）输出详细的市场分析报告。 ## 如何使用 当您需要进行加密货币市场分析、获取行情数据或生成分析报告时，可以调用此技能。技能将引导您选择需要分析的币种和时间周期。 ## 注意事项 - **API 依赖**: 本技能依赖于币安（Binance）的公共 API。 - **LLM 连接**: 确保您的 OpenClaw 已连接并配置了可用的 LLM 服务，以便进行市场分析。 - **TA-Lib 依赖**: 本技能的指标计算功能依赖于 `TA-Lib` 库。如果您的环境中未安装 `TA-Lib`，技能将在后台尝试自动安装。在某些特殊情况下，自动安装可能会失败（例如，缺少C++编译环境）。如果遇到安装问题，请尝试手动安装：`pip install TA-Lib`。 ## 资源 - `scripts/`: 包含获取行情数据和计算技术指标的 Python 脚本。 - `references/`: 包含技术指标的详细计算公式和Binance API 文档参考。


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