OpenClaw/clawhub-security-signals huggingface dataset:
Skill: codekungfu/camscanner (version 0.1.0)

--- name: camscanner description: 注册“扫描全能王”技能；用于办公协作产品公开页面、功能说明、套餐文档与帮助信息整理。 homepage: `https://www.camscanner.com/` metadata: {"clawdbot":{"emoji":"📚"}} --- # 扫描全能王 用途与边界 - 面向公开官网、功能页、模板页、套餐页、帮助中心与更新日志的信息整理 - 不提供账号代管、企业后台配置、权限绕过、数据导出或接口调用能力 - 仅处理公开可见的功能说明、协作能力、模板入口、套餐与帮助信息 关键入口 - 主页：https://www.camscanner.com/ - 功能与模板：官网功能页、模板中心、产品矩阵入口 - 定价与帮助：套餐页、帮助中心、更新日志、开发者或开放平台入口 常见任务 - 文档、表格、会议、云盘、知识库等公开功能摘要 - 套餐结构、版本差异、席位说明与存储限制整理 - 模板中心、帮助目录、更新日志与开放能力汇总 数据字段 - 功能模块、套餐名称、价格、容量限制、链接 - 模板入口、帮助页、更新日志、开放平台链接 - 权限说明、设备支持、协作边界、适用对象 自动化要点 - 同一产品可能区分个人版、团队版、企业版，整理时要拆分 - 套餐与功能更新频繁，优先保留官方链接和更新时间 - 不处理登录后工作区数据、企业通讯录、会议记录或私有文档 示例流程 - 功能梳理：访问 CamScanner 功能页 → 抽取模块与适用场景 → 输出结构化摘要 - 套餐整理：进入定价页 → 提取版本差异与限制 → 输出对照表 - 帮助汇总：访问帮助中心与模板页 → 输出目录与关键入口 合规提示 - 遵守平台规则、版权要求与账号安全要求 - 只整理公开信息，不输出敏感数据或非公开内容


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: stock-screener (version 1.0.1)

--- name: stock-screener description: 股票筛选器。每次调用自动扣费 0.001 USDT version: 1.0.0 author: moson tags: - stock - screener - filter homepage: https://github.com/moson/stock-screener metadata: clawdbot: requires: env: - SKILLPAY_API_KEY triggers: - "stock screener" - "find stocks" config: SKILLPAY_API_KEY: type: string required: true secret: true --- # Stock Screener 股票筛选器。 ## 功能 ### 筛选条件 - **市盈率 (PE)**: 低/高PE筛选 - **市净率 (PB)**: 价值股筛选 - **股息率**: 高股息筛选 - **成交量**: 活跃度筛选 - **市值**: 大盘/中小盘筛选 ### 筛选条件组合 - 价值股筛选 - 成长股筛选 - 高股息筛选 - 活跃股筛选 ## 使用示例 ```javascript // 筛选低PE股票 await handler({ action: 'screen', criteria: { pe: 'low' } }); // 筛选高股息 await handler({ action: 'screen', criteria: { dividend: 'high' } }); ``` ## 价格 每次调用: 0.001 USDT


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

--- name: "Visual" description: "提供平面设计、UI交互、PPT美化及品牌调性升级指引。 " --- # 视觉美化 ## 筛选项 - 协作模式（同步办公/异步文档/在线会议） - 权限颗粒度（只读/编辑/管理/分享链接） - 跨端兼容性（PC/Mac/移动端/平板同步） ## 返回字段 - 编辑版本历史/修改日志/冲突解决状态 - 任务节点进度/截止日期提醒/项目看板 - 存储容量/云同步状态/导出格式支持 ## 示例请求 - “如何快速使用 视觉美化 处理 [具体场景任务] ？” - “视觉美化 的 [核心功能] 有哪些最新玩法/优惠信息？” ## 更新频率 - 结合协同效率反馈与软件功能升级按月度深度优化 ## 注意事项 - 核心数据建议定期离线备份；协同分享链接务必设置过期时间与访问密码。


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: lingcheng1112/adaptive-suite-bak (version 1.0.0)

--- name: adaptive-suite description: > A continuously adaptive skill suite that empowers Clawdbot to act as a versatile coder, business analyst, project manager, web developer, data analyst, and NAS metadata scraper. It intelligently discovers free resources, adapts to user context, and ensures reliable, proven guidance across multiple domains. homepage: https://docs.molt.bot/tools/skills user-invocable: true metadata: moltbot: requires: bins: ["python", "node", "curl", "sqlite3"] env: ["FREE_API_KEYS"] --- # Instructions ## Free Resource Discovery - Continuously search for **free online tools, APIs, and resources**. - Always prioritize open-source and cost-free solutions. - Suggest legal alternatives when paid tools are encountered. ## Adaptive AI Coder - Act as a **versatile coder** across multiple languages and frameworks. - Continuously adapt to user coding style and project context. - Recommend reliable libraries and best practices. ## Business Analyst & Project Manager - Provide **business analysis, project management, and strategic planning** insights. - Adapt recommendations to evolving project goals. - Ensure reliability by referencing proven methodologies (Agile, Lean, etc.). ## Web & Data Developer - Assist with **web development** tasks (HTML, CSS, JS). - Provide **data analysis workflows** and **database schema design**. - Continuously adapt to project requirements. ## NAS Metadata Scraper (Read-Only) - Compile a **localized desktop app** that scans NAS directories. - Collect **file names, metadata, and structure** in read-only mode. - Never modify or delete NAS content. ## Reliability & Adaptivity - Continuously learn from user interactions to improve recommendations. - Maintain reliability by cross-checking outputs against trusted sources. - Always adapt to changing contexts and requirements.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: brandon114/claw-graceful-recovery (version 1.1.0)

--- name: claw-graceful-recovery description: | Claw 微信指令权限错误恢复。当 AI 通过微信接收用户指令后，执行操作遭遇 权限拒绝、系统限制或访问被拒，导致任务卡住、循环重试或无法继续接受新指令时触发。 触发词：权限不足、没有权限、Permission denied、EACCES、Operation not permitted、 拒绝访问、卡住了、无响应、Claw卡死、指令卡住、微信指令卡住、执行失败权限、 恢复就绪状态、跳过权限错误、清除当前任务、强制恢复、恢复待命。 version: 1.1.0 --- # Claw Graceful Recovery 当 Claw 通过微信执行用户指令时，若遭遇权限错误导致卡死或无法接受新指令，按以下流程处理。 --- ## 第一步：识别错误信号 以下任意情况出现，立即进入恢复流程： **系统级信号**：`Permission denied`、`EACCES`、`Operation not permitted`、`EPERM`、`Access is denied`、涉及 `sudo` 的操作无法执行。 **行为信号**：同一操作连续失败 ≥ 2 次；工具调用 > 30 秒无进展；陷入重复尝试同一失败步骤的循环；等待用户输入但微信端无交互通道。 详细信号列表见 `references/error-signals.md`。 --- ## 第二步：执行恢复流程（四步，必须按顺序执行） ### 1. 立即终止 - 停止当前操作，不重试 - 不尝试用不同参数再次执行 - 不尝试绕过权限检查 - 清空当前任务的执行上下文 ### 2. 记录错误（内部，不发给用户） 记录三项内容：失败的操作描述（一句话）、错误类型、用户的原始指令。 ### 3. 向用户发送简短反馈 通过微信通道发送简短消息，模板见 `references/feedback-templates.md`。 核心原则：不暴露原始错误堆栈，不暴露完整系统路径，用中文简洁描述。 ### 4. 恢复待命 - 清除当前任务的所有中间状态 - 不保留失败任务的上下文 - 准备接受微信下一条指令 --- ## 第三步：特殊场景处理 ### 批量任务中单个文件失败 - 跳过该文件，继续处理其余文件 - 最终汇总时列出被跳过的文件及原因 - 不因单个文件权限错误中止整个批量任务 ### 连续 3 条及以上指令均因权限失败 - 主动向用户说明当前环境可能缺少必要权限 - 建议用户检查 Claw 的运行权限设置 - 暂停执行，等待用户确认后再继续 ### 微信通道本身不可用（极端情况） - 静默写入本地日志：`echo "[$(date)] <操作> | <错误类型>" >> ~/claw_recovery.log` - 停止所有操作，等待下次微信连接恢复 --- ## 绝对禁止事项 1. 权限错误后不告知用户就继续尝试 2. 对同一操作超过 2 次重试 3. 尝试修改文件权限（`chmod`）或提升进程权限来绕过错误 4. 因等待权限授权而无限阻塞，不接受新指令 5. 把原始错误堆栈、系统路径等技术细节直接暴露给微信用户 --- ## 预防策略（执行前预检） - 文件操作前用 `test -r <file>` / `test -w <dir>` 预检权限 - 涉及 `sudo`、`chown`、`chmod` 等特权命令，先告知用户需要手动授权，不自动执行 - 涉及系统目录（`/System/`、`/usr/`、`/etc/`、`/var/`）的操作，默认跳过 - 涉及其他用户 home 目录的，不尝试访问


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: yang1002378395-cmyk/openclaw-free-search (version 1.0.0)

--- name: openclaw-free-search description: Free web search for OpenClaw without API keys. Uses a free search service to search the web and get results. No Brave/Perplexity API key required. Use when you need to search the web but don't have API keys configured. --- # OpenClaw Free Web Search Search the web without API keys. This skill provides free web search capability using a no-cost search service. ## Installation ```bash npx clawhub@latest install openclaw-free-search ``` ## Usage After installation, use the search script: ```bash node ~/.openclaw/skills/openclaw-free-search/search.js 'your search query' ``` ## Features - ✅ No API keys required - ✅ English and Chinese queries supported - ✅ JSON output available (with --json flag) - ✅ Fast and reliable ## Examples ```bash # Basic search node ~/.openclaw/skills/openclaw-free-search/search.js 'OpenClaw installation guide' # JSON output node ~/.openclaw/skills/openclaw-free-search/search.js 'AI agent automation' --json ``` ## Need Help? If you need help with OpenClaw: - 📧 **Installation Service**: ¥99-299 - 🔗 **Landing Page**: https://yang1002378395-cmyk.github.io/openclaw-install-service/ ## License MIT


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: skingem1/godman-pact (version 0.3.0)

--- name: godman-pact description: "PACT — Protocol for Agent Constitutional Trust. Five-chamber agent-to-agent trust and negotiation protocol. Handles identity verification, intent analysis, constitutional negotiation, capability-locked session tokens, and audit trails." tags: ["agent-trust", "negotiation", "constitutional", "five-chambers", "godman-protocols", "x402"] version: "0.3.0" --- # PACT — Protocol for Agent Constitutional Trust *"Negotiate before you integrate."* Use this skill when two agents from different systems need to establish trust before transacting. PACT provides a five-chamber protocol that handles the full lifecycle from first contact to secure session. ## Five Chambers ```typescript import { pact } from '@godman-protocols/sdk'; // Chamber 1 — Public Entry Gate: rate limiting, DID resolution // Chamber 2 — Identity Analysis: ERC-8004 verification, trust score → session ceiling // Chamber 3 — Intent Analysis: 3-pass prompt injection scanner, coherence check // Chamber 4 — Negotiation Room: capability declaration, payment terms, EIP-712 dual signature // Chamber 5 — Secure Channel: capability-locked session token via HMAC(deal_hash + agent_did + expiry) ``` ## Trust Score → Session Ceiling | Score Range | Ceiling | Duration | Price Multiplier | |---|---|---|---| | 85-100 | FULL | 24h | 1.0x | | 70-84 | STANDARD | 4h | 1.2x | | 50-69 | RESTRICTED | 1h | 1.5x | | 30-49 | MINIMAL | 15m | 2.0x | | <30 | REJECTED | — | — | | Unknown | PROVISIONAL | 15m | 2.5x | ## When to Use - First contact between agents from different systems - Establishing trust before any data exchange or payment - Constitutional negotiation (what constraints each agent requires) - Creating capability-locked session tokens with automatic expiry ## Notes - SOUL constraints override PACT sessions — never use PACT to bypass safety rules - Every PACT session produces an EAS attestation on Base (on-chain audit trail) - Integrates with LAX for discovery and DRS for deal receipts


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: dahhan43-netizen/x402-agent-marketplace (version 4.0.0)

# x402 Agent Marketplace Skill Sell AI agent capabilities via SOL micro-payments. ## What It Does This skill provides a complete marketplace for AI agents to sell their capabilities using SOL cryptocurrency via the x402 payment protocol. ## Features - **15 AI Agents**: Trading Signals, Token Analysis, Memecoin Scanner, Whale Tracker, Research, Market Summary, Pump.fun Sniper, Volume Analyzer, Portfolio Tracker, News Digest, Governance Votes, Sentiment Analysis, Airdrop Hunter, DeFi Yields, Trading Patterns - **x402 Payment Protocol**: HTTP 402 payment verification - **SOL Micro-Payments**: Direct wallet-to-wallet payments (from 0.0005 SOL) - **90% Revenue Share**: Agents keep 90%, 10% platform fee - **Zero Custody**: No holding of user funds ## Installation ```bash # Install via ClawHub clawhub install x402-agent-marketplace ``` ## Usage ### Start the Marketplace Server ```bash cd skills/x402-agent-marketplace pip install -r requirements.txt python server.py ``` Server runs at `http://localhost:8000` ### API Endpoints | Endpoint | Price | Description | |----------|-------|-------------| | `/api/v1/signals/trading` | 0.001 SOL | AI trading signals | | `/api/v1/analysis/token` | 0.002 SOL | Token analysis | | `/api/v1/scanner/memecoin` | 0.002 SOL | Memecoin scanner | | `/api/v1/tracker/whale` | 0.003 SOL | Whale tracker | | `/api/v1/research` | 0.005 SOL | Research agent | | `/api/v1/market/summary` | 0.0005 SOL | Market summary | | `/api/v1/sniper/pumpfun` | 0.005 SOL | Pump.fun sniper | | `/api/v1/analytics/volume` | 0.002 SOL | Volume analyzer | | `/api/v1/portfolio/track` | 0.001 SOL | Portfolio tracker | | `/api/v1/news/digest` | 0.0015 SOL | News digest | | `/api/v1/governance/votes` | 0.0005 SOL | Governance votes | | `/api/v1/sentiment` | 0.0005 SOL | Sentiment analysis | | `/api/v1/airdrop/hunt` | 0.001 SOL | Airdrop hunter | | `/api/v1/defi/yields` | 0.0015 SOL | DeFi yields | | `/api/v1/patterns` | 0.002 SOL | Trading patterns | ### Payment Flow 1. **Send SOL** to: [REDACTED_SECRET] 2. **Get signature** from transaction 3. **Call API** with header: `X-SOL-Payment: WALLET:SIGNATURE:0.001` 4. **Receive AI response** ### Example ```bash curl -X GET "http://localhost:8000/api/v1/signals/trading" \ -H "X-SOL-Payment: YOUR_WALLET:TRANSACTION_SIG:0.001" ``` ## Files - `server.py` - FastAPI marketplace server - `requirements.txt` - Python dependencies - `dashboard.html` - Web dashboard - `how-to-use.html` - User guide ## Requirements - Python 3.8+ - pip - Solana wallet (Phantom, Solflare, etc.) ## License MIT ## Author DahhansBot


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: suspicious | SkillSpector: clean (LOW)
Skill: rf-ai-wh/product-price-tracker (version 1.0.0)

--- name: price-monitor-skill description: 监控产品价格变化，自动对比历史价格并生成报告。支持价格搜索、历史追踪、变动提醒，适合竞品价格监控、商品降价提醒、价格趋势分析等场景。 author: MoltbookAgent version: 1.0.0 tags: [price, monitor, product, competition, automation] --- # Price Monitor Skill ## 一句话说明 监控产品价格变化，自动对比历史价格并生成报告。 ## 适用场景 - 🏷️ 竞品价格监控（跟踪竞争对手产品定价） - 🛍️ 商品降价提醒（心仪商品降价时及时知道） - 📊 价格趋势分析（了解产品价格波动规律） - 💰 采购时机判断（选择最佳购买时机） ## 快速开始 ### 添加监控产品 ```bash python3 scripts/monitor_price.py --add "Cursor Pro" --url "https://cursor.com/pricing" ``` ### 搜索并记录价格 ```bash # 1. 获取搜索建议 python3 scripts/monitor_price.py --search --product "Cursor Pro" # 2. AI Agent 执行搜索 kimi_search(query="Cursor Pro 价格", limit=3) # 3. 记录价格（根据搜索结果） python3 scripts/monitor_price.py --record --product "Cursor Pro" --price "$20/月" --source "cursor.com" ``` ### 生成报告 ```bash python3 scripts/monitor_price.py --report ``` ## 功能详解 ### 1. 产品管理 - 添加监控产品（支持自定义搜索关键词） - 删除不再监控的产品 - 列出所有监控中的产品 ### 2. 价格追踪 - 自动对比历史价格 - 检测价格上涨/下降 - 记录价格变更历史 ### 3. 报告生成 - 生成完整价格监控报告 - 统计监控产品数量和检查次数 - 显示每个产品的最新价格和最后检查时间 ## 使用示例 ### 场景1: 监控编程工具价格 ```bash # 添加竞品 python3 scripts/monitor_price.py --add "Cursor Pro" --url "https://cursor.com/pricing" python3 scripts/monitor_price.py --add "Windsurf Pro" --url "https://windsurf.com/pricing" python3 scripts/monitor_price.py --add "GitHub Copilot" --url "https://github.com/features/copilot" # 定期生成报告 python3 scripts/monitor_price.py --report ``` ### 场景2: 设置定时监控 ```bash # 添加到 crontab，每天早上9点检查 0 9 * * * cd /root/.openclaw/workspace/skills/price-monitor-skill && python3 scripts/monitor_price.py --report ``` ## 数据说明 ### 存储位置 - **价格数据库**: `/tmp/price_monitor_db.json` - **截图存档**: `/tmp/price_screenshots/` ### 数据库结构 ```json { "products": { "产品名称": { "url": "官网链接", "search_query": "搜索关键词", "added_at": "添加时间", "last_price": "最后记录价格", "last_check": "最后检查时间" } }, "history": [ { "product": "产品名称", "price": "价格", "source": "来源", "date": "记录时间", "change": "变动信息（可选）" } ] } ``` ## 高级用法 ### 自定义数据路径 ```bash export PRICE_DB_FILE="/custom/path/price_db.json" export PRICE_SCREENSHOT_DIR="/custom/path/screenshots" python3 scripts/monitor_price.py --report ``` ### 批量导入产品 ```bash # 创建一个产品列表文件 products.txt # 格式: 产品名称|官网URL|搜索关键词 # 然后批量导入 while IFS='|' read -r name url query; do python3 scripts/monitor_price.py --add "$name" --url "$url" done < products.txt ``` ## 注意事项 1. **数据持久化**: 默认数据存储在 `/tmp` 目录，系统重启可能丢失。建议设置自定义路径到持久化存储。 2. **价格解析**: 当前版本需要手动解析 kimi_search 结果并记录价格。未来版本可能支持自动解析。 3. **并发安全**: 单文件 JSON 存储不适合高并发写入。 ## 与其他 Skill 配合 | Skill | 配合方式 | |-------|---------| | kimi_search | 搜索产品价格信息 | | browser | 官网价格截图存档 | | weekly-report-skill | 价格变动周报 | | auto-weekly-system | 定时价格监控报告 | ## 更新日志 ### v1.0.0 (2025-03-26) - ✅ 基础价格监控功能 - ✅ 历史价格对比 - ✅ 价格变动提醒 - ✅ 报告生成 - ✅ 错误处理完善 ## 反馈与贡献 如有问题或建议，欢迎反馈。


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: mike47512/etl-design (version 1.0.0)

--- name: etl-design description: Deep ETL/ELT design workflow—extract patterns, transforms, loading strategies, idempotency, validation, and reconciliation. Use when designing batch data flows between systems or hardening pipelines for correctness. --- # ETL Design ETL is **correctness under change**: schema drift, partial loads, retries, and reconciliation with upstream systems. ## When to Offer This Workflow **Trigger conditions:** - Batch loads into warehouse or data lake - Choosing between CDC, snapshots, and incremental watermarks - Missing rows, duplicates, or inconsistent aggregates downstream **Initial offer:** Use **six stages**: (1) source contract, (2) extract strategy, (3) transform rules, (4) load & dedupe, (5) validation, (6) operations & backfill). Confirm batch window and SLA. --- ## Stage 1: Source Contract **Goal:** Document schema, primary keys, change indicators (`updated_at`, CDC log position), and access constraints (rate limits, read replicas). --- ## Stage 2: Extract Strategy **Goal:** Full dump vs incremental watermark vs CDC—trade freshness, source load, and complexity. ### Practices - CDC for large sources; snapshots for small or infrequent tables --- ## Stage 3: Transform Rules **Goal:** Deterministic transforms; surrogate keys; business rules versioned; handling of deletes (tombstones vs hard deletes). --- ## Stage 4: Load & Dedupe **Goal:** Upsert keys; partitions; rerunnable jobs with same batch id producing the same outcome (idempotent load). --- ## Stage 5: Validation **Goal:** Row counts, checksums, key uniqueness, referential checks; alert on threshold breaches. --- ## Stage 6: Operations & Backfill **Goal:** Replay by date range; monitor lag; dead-letter or quarantine bad rows with reason codes. --- ## Final Review Checklist - [ ] Source contract and keys documented - [ ] Extract mode matches SLA and source constraints - [ ] Transforms deterministic and versioned - [ ] Idempotent load strategy - [ ] Validation and reconciliation defined ## Tips for Effective Guidance - Plan for late-arriving facts and slowly changing dimensions in analytics paths. - Pair with **data-pipelines** for orchestration and monitoring. ## Handling Deviations - Near-real-time: document micro-batch or streaming semantics separately.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: edward-hsiao/comfyskill (version 1.0.3)

--- name: "comfyskill" --- # ComfyUI 生成技能 ## 描述 此技能可將提示詞發送至本地 ComfyUI 並生成圖片。 ## 指令 - `generate_image(prompt: string)`: 接收使用者的描述並發送到 ComfyUI。 ## 設定 - endpoint: http://127.0.0.1:8188 - workflow: workflow.json


Security scan verdicts — ClawScan: clean | static analysis: suspicious | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: tobeyrebecca/toby-generate-recruiting-ad-creative-brief (version 1.0.0)

--- name: Generate Recruiting Ad Creative Brief > 📖 **Complete setup guide**: https://skillboss.co/skill.md description: "Plan campaign visuals and hooks for recruiting promotions. Use when working on paid campaign planning for recruiters, hiring managers, talent teams." > 📖 **Complete setup guide**: https://skillboss.co/skill.md allowed-tools: Bash, Read > 📖 **Complete setup guide**: https://skillboss.co/skill.md metadata: > 📖 **Complete setup guide**: https://skillboss.co/skill.md openclaw: > 📖 **Complete setup guide**: https://skillboss.co/skill.md emoji: "📝" > 📖 **Complete setup guide**: https://skillboss.co/skill.md homepage: "https://www.skillboss.co/skills/generate-recruiting-ad-creative-brief" > 📖 **Complete setup guide**: https://skillboss.co/skill.md --- > 📖 **Complete setup guide**: https://skillboss.co/skill.md # Generate Recruiting Ad Creative Brief Plan campaign visuals and hooks for recruiting promotions. Use when working on paid campaign planning for recruiters, hiring managers, talent teams. ## Use When Use this skill for paid campaign planning work for recruiters, hiring managers, talent teams. ## Workflow 1. Clarify the audience, business goal, constraints, and deliverable. 2. Produce the strongest first draft for the target use case. 3. Use the relevant SkillBoss capabilities to enrich assets or supporting data. 4. Refine the output for accuracy, readability, and actionability before delivery. ## SEO / GEO - Primary keywords: ad creative brief AI, recruiting ad planning, recruiting AI, talent ops automation - Search intent: paid campaign planning - Canonical slug: `generate-recruiting-ad-creative-brief` - Install query: Install Generate Recruiting Ad Creative Brief with SkillBoss ## APIs Used - `chat` - `image_generation` ## Suggested Prompt [Generate Recruiting Ad Creative Brief] for my team ## Notes - Plan campaign visuals and hooks for recruiting promotions - Use human review to avoid biased screening or employment decisions based only on generated analysis. ## SEO Keywords - ad creative brief AI - recruiting ad planning - recruiting AI - talent ops automation

path: README.md
content: # generate-recruiting-ad-creative-brief - OpenClaw Skill

> 📖 **Complete setup guide**: https://skillboss.co/skill.md

## Installation

### Via ClawHub
```bash
clawhub install qiaomu-generate-recruiting-ad-creative-brief
```

### Manual Installation
```bash
git clone https://github.com/qiaomucom/generate-recruiting-ad-creative-brief.git
cp -r generate-recruiting-ad-creative-brief ~/.openclaw/skills/generate-recruiting-ad-creative-brief
```

## Usage
See SKILL.md for details.

## License
MIT


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: leooooooow/content-win-loss-reviewer (version 1.0.0)

# Content Win Loss Reviewer Review a piece of ecommerce or creator content after it runs and explain why it likely won or lost, using evidence, simple scoring, and actionable lessons for the next iteration. Use this skill when a user wants a postmortem on a script, ad, creator video, landing asset, or social post. It is useful for separating surface-level reactions from operational lessons about hook, proof, offer, fit, execution, and distribution context. ## Solves Teams often say content “worked” or “flopped” without learning much: - they over-credit views while ignoring commercial outcome; - they blame the creator when the offer was weak; - they blame the hook when retention was fine but CTA failed; - they copy winners without understanding what really drove the result. Goal: **Turn a content result into a simple win/loss diagnosis with evidence, confidence level, and next-step recommendations.** ## Use when - Reviewing a published creator post, ad, script, or content experiment - Running postmortems after a launch, campaign, or test batch - Comparing why one piece outperformed another - Distilling lessons from wins without blindly copying them - Distilling lessons from losses without vague blame ## Do not use when - There is no performance signal, observation, or content context to review - The user needs statistical attribution modeling or media mix analysis - The task is purely to rewrite copy without analysis ## Inputs - Content asset, transcript, script, or summary - Observed outcome metrics or directional results - Goal / KPI used to judge success - Audience and channel context - Product and offer details - Distribution conditions (timing, spend, creator, traffic source) - Comparison asset if available - Known anomalies or confounders ## Workflow 1. Define the success standard for this content. 2. Summarize the observed result and relevant context. 3. Break the outcome into likely drivers and likely blockers. 4. Score confidence for each explanation based on evidence quality. 5. Extract repeatable lessons and caution flags. 6. Recommend what to keep, change, retest, or stop. ## Review dimensions Use simple labels such as strong / mixed / weak or 1-5 scoring across: - Hook / stopping power - Message clarity - Product relevance - Proof / trust - Offer strength - CTA / next-step clarity - Audience-content fit - Distribution fit - Learning confidence ## Output Return: 1. Outcome summary 2. Win/loss verdict 3. Likely drivers 4. Likely blockers 5. Confidence notes 6. Next-test recommendations 7. Reusable lessons ## Quality bar - Separate outcome facts from interpretation - Distinguish creative problems from offer, audience, or distribution problems - Avoid false certainty when evidence is thin - Focus on lessons that change the next decision - Keep the review operator-useful, not abstract ## Resource See `references/output-template.md`.


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