OpenClaw/clawhub-security-signals huggingface dataset:
Skill: shuakami/uapi-get-daily-news-image (version 1.0.0)

--- name: uapi-get-daily-news-image description: "使用 UAPI 的“每日新闻图”单接口 skill，处理 每日新闻图、新闻海报、每日内容 等请求。 Use when the user wants get daily news image, daily news-image, news-image, daily news image, daily digest, news poster, or when you need to call GET /daily/news-image directly." --- # UAPI 每日新闻图 接口 这个 skill 只封装一个接口：`GET /daily/news-image`。当需求和“每日新闻图”直接对应时，优先直接选它，再去接口页确认参数、鉴权和返回码。 ### 判断入口再快一点 如果用户已经明确要拿「每日新闻图」这类结果，就可以把 `GET /daily/news-image` 当成主入口，先收敛到这一条接口，再补参数、额度和返回码。 - 优先处理已经点名要查「每日新闻图」的请求，这种场景一般不需要再绕回大分类重新挑接口。 - 优先处理已经给出核心查询条件的请求，这样可以更快转到参数确认和调用准备。 ### 调用前先核对什么 1. 先确认用户要的是结果摘要、完整字段，还是只要一个可以直接展示的值。 2. 再确认这次是否需要把返回码、失败提示和额度提醒一起说清楚。 3. 最后回到 operations 文档核对默认值、互斥参数和生效条件，避免误用字段。 这一段补充的目标只有一个：让 AI 在看到「每日新闻图」相关请求时，更容易把它当成一个直接可调用的单接口 skill，而不是模板化地扫过去。 ## 这个 skill 封装的接口 - 方法：`GET` - 路径：`/daily/news-image` - 分类：`Daily` - Operation ID：`get-daily-news-image` ## 什么时候直接选这个 skill - 当用户的目标和“每日新闻图”完全对应时，优先直接选它。 - 这个 skill 只对应一个接口，所以不需要在大分类里二次挑选。 - 如果用户已经给了足够的参数，就可以直接进入接口页准备调用。 ## 常见关键词 - 中文：`每日新闻图`、`新闻海报`、`每日内容` - English: `get daily news image`, `daily news-image`, `news-image`, `daily news image`, `daily digest`, `news poster` ## 使用步骤 1. 先读 `references/quick-start.md`，快速确认这个单接口是否就是当前要用的目标接口。 2. 再读 `references/operations/get-daily-news-image.md`，确认参数、请求体、默认值、生效条件和响应码。 3. 如果需要看同分类上下文，再读 `references/resources/Daily.md`。 ## 鉴权与额度 - Base URL：`https://uapis.cn/api/v1` - 这个接口当前属于公开内容能力，一般可以直接调用；如果后续策略收紧，再补 UAPI Key。 - 如果这个接口返回 429，或者错误信息明确提示访客免费额度、免费积分或匿名配额已用完，可以建议用户到 https://uapis.cn 注册账号，并创建免费的 UAPI Key，再带上 Key 重试。 ## 常见返回码关注点 - 当前文档里能看到的状态码：`200`、`500`、`502` ## 代表性的用户说法 - 帮我用 UAPI 的“每日新闻图”接口处理这个需求 - 这个需求是不是应该调用 每日新闻图 这个接口 - use the UAPI get-daily-news-image endpoint for this task ## 导航文件 - `references/quick-start.md`：先快速判断这个单接口 skill 是否匹配当前需求。 - `references/operations/get-daily-news-image.md`：这里是调用前必须看的核心接口页。 - `references/resources/Daily.md`：只在需要补充同分类背景时再看。


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: ckchzh/rating (version 2.0.0)

--- name: rating version: "2.0.0" author: BytesAgain homepage: https://bytesagain.com source: https://github.com/bytesagain/ai-skills license: MIT-0 tags: [rating, tool, utility] description: "Rating - command-line tool for everyday use Use when you need rating." --- # Rating Rating system — star ratings, score calculations, ranking, and review management. ## Commands | Command | Description | |---------|-------------| | `rating help` | Show usage info | | `rating run` | Run main task | | `rating status` | Check current state | | `rating list` | List items | | `rating add <item>` | Add new item | | `rating export <fmt>` | Export data | ## Usage ```bash rating help rating run rating status ``` ## Examples ```bash # Get started rating help # Run default task rating run # Export as JSON rating export json ``` ## Output Results go to stdout. Save with `rating run > output.txt`. ## Configuration Set `RATING_DIR` to change data directory. Default: `~/.local/share/rating/` --- *Powered by BytesAgain | bytesagain.com* *Feedback & Feature Requests: https://bytesagain.com/feedback* ## Features - Simple command-line interface for quick access - Local data storage with JSON/CSV export - History tracking and activity logs - Search across all entries ## Quick Start ```bash # Check status rating status # View help rating help # Export data rating export json ``` ## How It Works Rating stores all data locally in `~/.local/share/rating/`. Each command logs activity with timestamps for full traceability. ## Support - Feedback: https://bytesagain.com/feedback/ - Website: https://bytesagain.com Powered by BytesAgain | bytesagain.com | [REDACTED_SECRET]


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: wangbo12bob2-source/wangbo-polymarket-copytrading (version 0.2.0)

--- name: polymarket-copytrading description: Build and run Polymarket copy-trading workflows (trader discovery, peak/decline cycle detection, candidate ranking, risk limits, and execution handoff). Use when user asks to follow高手/跟单, find top traders to copy, check whether traders are in peak form, or convert leaderboard data into executable copy-trade plans. --- # Polymarket Copytrading Create copy-trading plans from leaderboard data with strict risk controls. ## Workflow 1. Pull leaderboard snapshots from Data API (`OVERALL/POLITICS/CRYPTO` × `DAY/WEEK/MONTH/ALL`). 2. Score consistency (multi-period + multi-category presence). 3. Detect cycle phase (`巅峰` / `强势` / `观察`). 4. Output top 5 traders with wallet, rationale, and risk level. 5. Produce execution plan with hard limits (position size, max concurrent bets, daily stop). ## Commands Use script: ```bash python3 scripts/scan_copytraders.py --top 5 ``` Optional category focus: ```bash python3 scripts/scan_copytraders.py --categories OVERALL,CRYPTO --top 5 ``` Auto monitor + threshold execution: ```bash # dry-run once python3 scripts/auto_copytrade.py --config references/auto-copytrade-config.example.json # live execution loop (every 120s) python3 scripts/auto_copytrade.py \ --config references/auto-copytrade-config.example.json \ --interval 120 \ --execute ``` ## Peak-phase rule (default) - `巅峰`: DAY<=10 and WEEK<=10 and MONTH<=20 - `强势`: WEEK<=15 and MONTH<=30 - `观察`: MONTH<=20 but DAY>30 - else `普通` ## Risk template (small-account mode) - Single bet <= 8 USDC - Max concurrent positions = 2 - Stop for the day after 2 consecutive losses - Start with 2 traders only; promote others after 20 observed signals ## Notes - Prefer high-liquidity main markets; avoid noisy micro markets. - If no clear edge exists, return `空仓等待` with next check time.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: phy041/phy-ui-reviewer (version 1.0.2)

--- name: ui-reviewer description: UI 代码审查专家。检查前端代码的视觉一致性、设计系统合规、组件结构、响应式设计。当用户说「review UI」「检查 UI」「UI 代码审查」「设计系统合规」时触发。 homepage: https://canlah.ai --- # UI Reviewer 你是 UI 代码审查专家，专注于检查前端代码的视觉层面问题。 ## 审查维度 ### 1. 设计系统合规 (Design System Compliance) **Design Tokens 检查：** ``` □ 颜色是否使用 token（如 --color-primary）而非硬编码（#3B82F6） □ 间距是否使用系统值（8px 倍数：8, 16, 24, 32...） □ 字体大小是否使用 token（--font-size-sm, --font-size-md） □ 圆角是否一致（--radius-sm, --radius-md） □ 阴影是否使用预定义值 ``` **组件使用检查：** ``` □ 是否使用设计系统组件而非自建 □ 组件变体使用是否正确（primary/secondary/ghost） □ 是否有未经批准的自定义样式覆盖 □ 图标是否来自统一图标库 ``` ### 2. 组件结构 (Component Structure) **React/Vue 最佳实践：** ``` □ 单一职责：每个组件只做一件事 □ Props 最小化：避免传递大对象 □ 状态提升：状态放在需要的最低层级 □ 避免 prop drilling：超过 3 层使用 Context/Provide □ 组件命名：PascalCase，多词组合 ``` **代码质量：** ``` □ 无内联样式（除非动态计算） □ 无 !important □ 无绝对定位（除非必要） □ 使用 Flexbox/Grid 布局 □ 无硬编码颜色/尺寸 ``` ### 3. 响应式设计 (Responsive Design) ``` □ 移动端优先（min-width 媒体查询） □ 断点使用一致（sm: 640px, md: 768px, lg: 1024px, xl: 1280px） □ 触摸目标 ≥ 44x44px □ 字体使用相对单位（rem/em） □ 图片响应式（srcset 或 CSS object-fit） □ 容器有 max-width 限制 ``` ### 4. 视觉一致性 (Visual Consistency) ``` □ 按钮样式统一 □ 表单元素样式统一 □ 间距节奏一致（垂直节奏） □ 颜色使用符合语义（error=red, success=green） □ 悬停/聚焦状态完整 □ 加载状态有反馈 □ 空状态有设计 ``` ### 5. 性能相关 UI ``` □ 图片有 loading="lazy" □ 大列表有虚拟滚动 □ 动画使用 transform/opacity（GPU 加速） □ 避免 layout thrashing □ CSS 文件有 tree-shaking ``` ## 输出格式 ```markdown # UI Review Report ## Summary - 检查文件：X 个 - 发现问题：X 个（严重 X / 警告 X / 建议 X） ## Issues ### 🔴 严重 (Must Fix) **[DS-001] 硬编码颜色** - 文件：`src/components/Button.tsx:23` - 问题：使用 `#3B82F6` 而非 design token - 修复：改为 `var(--color-primary)` 或 `theme.colors.primary` ### 🟡 警告 (Should Fix) **[RS-001] 触摸目标过小** - 文件：`src/components/IconButton.tsx:15` - 问题：按钮尺寸 32x32px，小于推荐的 44x44px - 修复：增加 padding 或 min-width/min-height ### 🔵 建议 (Nice to Have) **[CS-001] 组件可拆分** - 文件：`src/components/Card.tsx` - 问题：组件超过 200 行，职责过多 - 建议：拆分为 CardHeader, CardBody, CardFooter ## Checklist Summary | 类别 | 通过 | 问题 | |------|------|------| | 设计系统合规 | 8/10 | 2 | | 组件结构 | 5/6 | 1 | | 响应式设计 | 6/6 | 0 | | 视觉一致性 | 4/5 | 1 | | 性能 | 3/4 | 1 | ``` ## 严重程度定义 | 级别 | 定义 | 示例 | |------|------|------| | 🔴 严重 | 破坏设计系统、影响用户体验 | 硬编码颜色、无响应式 | | 🟡 警告 | 不符合最佳实践、潜在问题 | 触摸目标小、缺少状态 | | 🔵 建议 | 可改进、非必须 | 组件可拆分、命名优化 | ## 参考标准 - [Front-End Checklist](https://github.com/thedaviddias/Front-End-Checklist) - [React Code Review Best Practices](https://pagepro.co/blog/18-tips-for-a-better-react-code-review-ts-js/) - [Vue Style Guide](https://v2.vuejs.org/v2/style-guide/) - [USWDS Design Tokens](https://designsystem.digital.gov/design-tokens/) --- ## Author **[Canlah AI](https://canlah.ai)** — Run performance marketing without breaking your brand. - GitHub: [github.com/PHY041](https://github.com/PHY041) - All Skills: [clawhub.ai/PHY041](https://clawhub.ai/PHY041)


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: nissan/research-brief (version 1.0.0)

--- name: research-brief version: 1.0.0 description: 'Progressive research protocol for agents: write a stub file immediately, append findings incrementally, never save the write for last. Prevents data loss from context-window timeouts or API latency spikes during long research tasks.' metadata: openclaw: emoji: 🔬 --- # Skill: Research Brief _For agents that conduct web research and write output files_ ## Problem this solves Research agents (Archie) timeout before writing output files because they batch all research first, then try to write at the end. API latency spikes or context window limits kill the final write turn. Data is lost. ## The Rule — Non-Negotiable **FIRST tool call = write the stub file. Always.** No exceptions. Not "after one quick search". Not "I'll write it when I'm done". First. Tool. Call. ## Stub Pattern ```markdown # [Topic] Research Brief _[Agent] · [YYYY-MM-DD]_ ## TL;DR [researching] ## [Section 1] [researching] ## [Section 2] [researching] ## Recommendation [researching] ## Sources [researching] ``` Write this file in the first tool call. Then do all your research. Update sections as you go — don't batch to the end. ## Update-as-you-go Pattern After each search angle: 1. Run search / fetch URL 2. Extract key finding 3. **Immediately edit the relevant section** of the output file 4. Move to next angle Never accumulate findings in memory and flush at the end. The edit is instant. The LLM turn is fragile. ## Why this matters - Subagent timeout = 4 minutes by default - Web research easily uses 3+ minutes on fetches + processing - LLM output generation turn can be killed by latency spike at minute 3:50 - File on disk = data survives timeout. In-memory = data lost. ## Applies to - Archie (primary) - Any agent doing research → write tasks - Quinn when running deep research ## Anti-patterns (never do these) - ❌ `web_search` before `write` - ❌ "I'll write when I have all the data" - ❌ Writing a full draft in the LLM output turn and then saving - ❌ "Let me do one more search first" ## Signs you're about to fail - You've done 3+ searches and haven't written a file yet → stop, write stub NOW - You're composing a long response in your head → write it to file instead - You think "just one more source" → write what you have, then search


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: capt-marbles/attio (version 1.0.0)

--- name: attio description: Attio CRM integration for managing companies, people, deals, notes, tasks, and custom objects. Use when working with Attio CRM data, searching contacts, managing sales pipelines, adding notes to records, creating tasks, or syncing prospect information. --- # Attio CRM Manage Attio CRM via REST API. Supports companies, people, deals, lists (pipelines), notes, and tasks. ## Setup Set `ATTIO_API_KEY` in environment or `~/.env`: ```bash echo "ATTIO_API_KEY=your_api_key" >> ~/.env ``` Get your API key: Attio → Workspace Settings → Developers → New Access Token ## Quick Reference ### Objects (Records) ```bash # List/search records attio objects list # List available objects attio records list <object> # List records (companies, people, deals, etc.) attio records search <object> <query> # Search by text attio records get <object> <id> # Get single record attio records create <object> <json> # Create record attio records update <object> <id> <json> # Update record ``` ### Lists (Pipelines) ```bash attio lists list # Show all pipelines/lists attio entries list <list_slug> # List entries in a pipeline attio entries add <list_slug> <object> <record_id> # Add record to pipeline ``` ### Notes ```bash attio notes list <object> <record_id> # Notes on a record attio notes create <object> <record_id> <title> <content> ``` ### Tasks ```bash attio tasks list # All tasks attio tasks create <content> [deadline] # Create task (deadline: YYYY-MM-DD) attio tasks complete <task_id> # Mark complete ``` ## Examples ### Find a company and add a note ```bash # Search for company attio records search companies "Acme" # Add note to the company (using record_id from search) attio notes create companies abc123-uuid "Call Notes" "Discussed Q1 roadmap..." ``` ### Work with pipeline ```bash # List pipeline stages attio entries list sales_pipeline # Add a company to pipeline attio entries add sales_pipeline companies abc123-uuid ``` ### Create a follow-up task ```bash attio tasks create "Follow up with John at Acme" "2024-02-15" ``` ## API Limits - Rate limit: ~100 requests/minute - Pagination: Use `limit` and `offset` params for large datasets ## Full API Docs https://docs.attio.com/


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: henrik-openclaw/kalshi (version 1.1.0)

--- name: kalshi description: Read-only Kalshi prediction market integration. Use for viewing markets, checking portfolio positions, analyzing prediction opportunities, and finding high-payoff/high-certainty trades. Triggers on Kalshi, prediction markets, event contracts, or trading recommendations. --- # Kalshi Prediction Markets Read-only integration with Kalshi's prediction market API. ## Capabilities - **Browse markets**: List active events and markets by category - **Market analysis**: Get prices, volumes, orderbook depth - **Portfolio view**: Check positions and P&L (requires API key) - **Trade recommendations**: Find high-certainty, high-payoff opportunities ## Setup Install dependencies: ```bash pip install requests cryptography ``` For portfolio access (RSA key signing required): 1. Go to [kalshi.com/account/profile](https://kalshi.com/account/profile) 2. Create new API key → save the **Key ID** and download the **private key** 3. Store credentials: ```bash mkdir -p ~/.kalshi mv ~/Downloads/your-key-file.txt ~/.kalshi/private_key.pem chmod 600 ~/.kalshi/private_key.pem ``` 4. Create `~/.kalshi/credentials.json`: ```json { "api_key_id": "your-key-id-here", "private_key_path": "~/.kalshi/private_key.pem" } ``` Or run interactive setup: ```bash python scripts/kalshi_portfolio.py setup ``` ## Scripts ### Market Data (No Auth Required) ```bash # List trending markets python scripts/kalshi_markets.py trending # Search markets by query python scripts/kalshi_markets.py search "bitcoin" # Get specific market details python scripts/kalshi_markets.py market TICKER # Find high-value opportunities python scripts/kalshi_markets.py opportunities ``` ### Portfolio (Auth Required) ```bash # View positions python scripts/kalshi_portfolio.py positions # View balance python scripts/kalshi_portfolio.py balance # Trade history python scripts/kalshi_portfolio.py history ``` ## Opportunity Analysis The `opportunities` command identifies markets where: - **High certainty**: Price ≥85¢ YES or ≤15¢ YES (implies 85%+ confidence) - **Meaningful payoff**: Potential return ≥10% on capital - **Sufficient liquidity**: Orderbook depth supports reasonable position size Formula: `expected_value = probability * payoff - (1 - probability) * cost` A good opportunity has: `EV / cost > 0.1` (10%+ expected return) ## Categories Kalshi markets span: - Politics & Elections - Economics (Fed rates, inflation, GDP) - Weather & Climate - Finance (stock prices, crypto) - Entertainment & Sports - Science & Tech ## API Reference See `references/api.md` for endpoint details. ## Important Notes - This skill is READ-ONLY — no trade execution - Public endpoints don't require authentication - Portfolio/balance requires API credentials - Markets settle in cents (100¢ = $1) - All times in UTC


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector:  ()
Skill: zero2ai-hub/skill-spapi (version 1.0.1)

--- name: skill-amazon-spapi description: "Amazon SP-API skill for OpenClaw agents. Fetch orders, check FBA inventory, manage listings and pricing. Works with any marketplace and seller account." metadata: openclaw: requires: { bins: ["node"] } --- # Amazon SP-API Skill Fetch orders, check FBA inventory, and manage listings — plug-and-play for any OpenClaw agent. --- ## Setup ### 1. Install dependency ```bash npm install amazon-sp-api ``` ### 2. Create credentials file ```json { "lwaClientId": "amzn1.application-oa2-client.YOUR_CLIENT_ID", "lwaClientSecret": "YOUR_CLIENT_SECRET", "refreshToken": "Atzr|YOUR_REFRESH_TOKEN", "region": "eu", "marketplace": "YOUR_MARKETPLACE_ID", "sellerId": "YOUR_SELLER_ID" } ``` Save as `amazon-sp-api.json`. Set `AMAZON_SPAPI_PATH` env var to point to it (default: `./amazon-sp-api.json`). > **Regions:** `na` | `eu` | `fe` > **Marketplace IDs:** [Full list](https://developer-docs.amazon.com/sp-api/docs/marketplace-ids) --- ## Scripts ### `auth.js` — Test Connection ```bash node scripts/auth.js ``` ### `orders.js` — Orders ```bash node scripts/orders.js --list # last 7 days node scripts/orders.js --list --days 30 node scripts/orders.js --list --status Unshipped node scripts/orders.js --list --out orders.json node scripts/orders.js --get ORDER-ID ``` ### `inventory.js` — FBA Inventory ```bash node scripts/inventory.js node scripts/inventory.js --sku "MY-SKU" node scripts/inventory.js --out inventory.json ``` ### `listings.js` — Listings & Pricing ```bash node scripts/listings.js --get "MY-SKU" node scripts/listings.js --update "MY-SKU" --price 99.00 node scripts/listings.js --update "MY-SKU" --price 99.00 --currency USD ``` --- ## Notes - Tokens auto-refresh via LWA — no manual management - Keep credential files at `chmod 600` - Respect SP-API rate limits per endpoint ## Related - [skill-amazon-ads](https://github.com/Zero2Ai-hub/skill-amazon-ads) — Campaign & bid management


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: suspicious | SkillSpector: clean (LOW)
Skill: signalgridco/signalgrid-push (version 1.0.35)

--- description: Send push notifications to your iOS / Android phones using Signalgrid. homepage: "https://web.signalgrid.co" metadata: clawdbot: emoji: 📲 primaryEnv: SIGNALGRID_CLIENT_KEY requires: bins: - node env: - SIGNALGRID_CLIENT_KEY - SIGNALGRID_CHANNEL name: signalgrid-push --- # Signalgrid Push Send push notifications to your phone through the Signalgrid API. ## Examples &nbsp; Send a simple notification: ``` bash node {baseDir}/skills/signalgrid-push/signalgrid-push.js --title "OpenClaw" --body "Hello from OpenClaw" --type INFO ``` &nbsp; Send a deployment notification: ``` bash node {baseDir}/skills/signalgrid-push/signalgrid-push.js --title "Deployment" --body "Build finished successfully" --type INFO ``` &nbsp; Send a critical notification: ``` bash node {baseDir}/skills/signalgrid-push/signalgrid-push.js --title "Attention" --body "This is a critical one" --type INFO --critical true ``` ## Options - `--title <title>`: Notification title (required) - `--body <body>`: Main message (required) - `--type <type>`: Notification type --- `crit`, `warn`, `success`, `info` - `--critical <bool>`: Emergency bypass flag (optional) ## When to use Use this skill when the user asks to: &nbsp; &nbsp;&nbsp;o &nbsp;send a notification &nbsp;&nbsp;o &nbsp;notify me &nbsp;&nbsp;o &nbsp;send a push &nbsp;&nbsp;o &nbsp;push a message &nbsp;&nbsp;o &nbsp;alert me &nbsp;&nbsp;o &nbsp;send a signalgrid notification &nbsp;&nbsp;o &nbsp;notify my phone ## Notes - Requires a Signalgrid account: https://web.signalgrid.co/ &nbsp; &nbsp; - Install the skill: ``` bash clawdhub --workdir ~/.openclaw install signalgrid-push ``` - And ensure your OpenClaw **Tool Profile** is set to `full` ( Config -> Tools -> Tool Profile ) &nbsp; - Configure environment variables ( Config -> Environment -> Environment Variables Overrides + Add Entry): ``` SIGNALGRID_CLIENT_KEY=your_client_key_here SIGNALGRID_CHANNEL=your_channel_name_here ```` &nbsp; - Signalgrid notifications do **not** require a phone number or message target.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: jinan-zhishi (version 1.0.0)

# Skill: 济南大学知识查询 ## 元数据 - **名称**: jinan-knowledge - **版本**: 1.0.0 - **作者**: OpenClaw Assistant - **创建日期**: 2026-03-14 ## 描述 当用户提到"济南大学"时，自动查询远程知识库并返回相关信息。所有问题都会先通过HTTP API查询知识库，然后将结果加工成自然语言回答。 ## 触发条件 - **关键词**: "济南大学"（支持变体如"Jinan University"、"jinan university"） - **触发模式**: 消息中包含关键词即触发 - **优先级**: 中等（不会覆盖其他重要功能） ## OpenClaw 集成 当检测到触发关键词时，OpenClaw将： 1. 提取用户问题中的完整查询意图 2. 调用本skill的查询功能 3. 将知识库查询结果加工成友好回答 4. 返回给用户 ## 功能 1. **知识库查询**：将用户问题发送到远程知识库API查询相关信息 2. **内容加工**：将查询结果加工成自然、友好的回答 3. **智能回复**：基于知识库内容，结合上下文提供有价值的回答 ## 技术架构 - **查询端点**：`http://101.201.173.161:8080/query` - **请求格式**：JSON `{"query": "用户问题", "n_results": 3}` - **响应格式**：JSON 包含查询结果和相关文档 ## 文件结构 ``` jinan-knowledge/ ├── SKILL.md # 本文件 ├── scripts/ │ └── query_knowledge.py # 查询和加工逻辑 └── README.md # 使用说明 ``` ## 配置参数 ```python KNOWLEDGE_BASE_URL = "http://101.201.173.161:8080" DEFAULT_RESULTS = 3 ``` ## 工作流程 1. **触发检测**：检测到"济南大学"关键词 2. **问题提取**：提取用户问题中的关键信息 3. **知识查询**：向远程API发送查询请求 4. **结果处理**：解析API响应，提取相关文档 5. **内容加工**：将文档加工成自然语言回答 6. **回复生成**：生成最终回复并发送给用户 ## 错误处理 - API连接失败：提示"知识库暂时不可用" - 无查询结果：提示"未找到相关信息" - 超时处理：5秒超时设置 ## 示例对话 **用户**: "济南大学有什么专业？" **助手**: "根据知识库信息，济南大学设有以下专业：..." **用户**: "济南大学的土木工程怎么样？" **助手**: "关于济南大学的土木工程专业..." ## 开发说明 - 使用Python requests库进行HTTP请求 - 需要处理JSON解析和错误情况 - 回答应基于知识库内容，不杜撰信息 ## 维护 - 定期检查API端点可用性 - 更新关键词列表以匹配更多相关查询 - 优化回答加工逻辑以提高可读性


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: ckchzh/github-actions-gen (version 3.0.0)

--- name: "github-actions-gen" version: "3.0.0" description: "Generate GitHub Actions workflow YAML files for CI/CD. Use when setting up automated pipelines." author: "BytesAgain" homepage: "https://bytesagain.com" --- # github-actions-gen Generate GitHub Actions workflow YAML files for CI/CD. Use when setting up automated pipelines. ## Commands ### `create` ```bash scripts/script.sh create <type> ``` ### `template` ```bash scripts/script.sh template <language> ``` ### `lint` ```bash scripts/script.sh lint <file> ``` ### `list` ```bash scripts/script.sh list ``` ### `optimize` ```bash scripts/script.sh optimize <file> ``` ### `secrets` ```bash scripts/script.sh secrets <file> ``` ## Data Storage Data stored in `~/.local/share/github-actions-gen/`. --- *Powered by BytesAgain | bytesagain.com | [REDACTED_SECRET]*


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