[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6G7CP97SHAGMB53MB3KXRBG":3,"skill-same:01M6G7CP97SHAGMB53MB3KXRBG":54},{"skillNo":4,"name":5,"nameZh":6,"description":6,"descriptionZh":6,"repositoryFullName":7,"ownerLogin":8,"ownerAvatarUrl":9,"ownerAccountNo":10,"ownerDisplayName":6,"repositoryNo":11,"starsCount":12,"licenseSpdxId":13,"licenseFileUrl":6,"sourceHtmlUrl":14,"categories":15,"keywords":21,"publishedAt":23,"linkOnly":24,"markdownContent":25,"markdownBody":25,"frontMatter":26,"refName":27,"commitSha":28,"skillDirectory":29,"forksCount":30,"repositoryHtmlUrl":31,"repositoryHomepageUrl":6,"ownerHtmlUrl":32,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":33,"install":34,"resources":47},"01M6G7CP97SHAGMB53MB3KXRBG","wrynai-skill",null,"kbarbel640-del\u002Fskills","kbarbel640-del","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F255315490?v=4","01M6CJPPQGCCESXMG3K7BBGQ5J","01M6CJPPX2PB2BCZERFVM2C2B3",1,"MIT","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fwrynai\u002Fwrynai-skill\u002FSKILL.MD",[16],{"categoryNo":17,"categoryName":18,"taxonomyType":19,"taxonomyTypeDesc":20},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",[22],"wrynai skill","2026-11-10 10:12:30",false,"# WrynAI Web Crawling Skill\n\n## Overview\n\nThis skill enables OpenClaw to perform advanced web crawling and content extraction using the WrynAI SDK. It provides capabilities for multi-page crawling, content extraction, search engine results parsing, and intelligent data gathering from websites.\n\n## Core Capabilities\n\n- **Multi-page crawling** with depth and breadth control\n- **Content extraction** (text, markdown, structured data, links)\n- **Search engine results** parsing (SERP data)\n- **Screenshot capture** (viewport and full-page)\n- **Smart listing extraction** (e-commerce, directory pages)\n- **Pattern-based URL filtering** for targeted crawling\n\n## Prerequisites\n\n### Environment Setup\n\n```bash\n# Install the WrynAI SDK\npip install wrynai\n\n# Set your API key as environment variable\nexport WRYNAI_API_KEY=\"your-api-key-here\"\n```\n\n### API Key\n\nSign up at https:\u002F\u002Fwryn.ai to obtain an API key. The key must be set in the `WRYNAI_API_KEY` environment variable.\n\n## Usage Patterns\n\n### 1. Basic Website Crawling\n\nUse this when the user wants to crawl an entire website or section of a website.\n\n```python\nimport os\nfrom wrynai import WrynAI, WrynAIError\n\ndef crawl_website(url: str, max_pages: int = 10) -> dict:\n    \"\"\"\n    Crawl a website starting from the given URL.\n    \n    Args:\n        url: Starting URL for the crawl\n        max_pages: Maximum number of pages to crawl (hard limit: 10)\n    \n    Returns:\n        Dictionary containing crawl results with pages and their content\n    \"\"\"\n    api_key = os.environ.get(\"WRYNAI_API_KEY\")\n    if not api_key:\n        raise ValueError(\"WRYNAI_API_KEY environment variable required\")\n    \n    try:\n        with WrynAI(api_key=api_key) as client:\n            result = client.crawl(\n                url=url,\n                max_pages=min(max_pages, 10),  # Hard limit enforced\n                max_depth=3,\n                return_urls=True,\n            )\n            \n            return {\n                \"success\": result.success,\n                \"total_pages\": result.total_pages,\n                \"total_visited\": result.total_visited,\n                \"pages\": [\n                    {\n                        \"url\": page.page_url,\n                        \"content\": page.content,\n                        \"urls_found\": len(page.urls),\n                        \"discovered_urls\": page.urls[:10],  # First 10 URLs\n                    }\n                    for page in result.pages\n                ],\n            }\n    except WrynAIError as e:\n        return {\n            \"success\": False,\n            \"error\": str(e),\n            \"status_code\": getattr(e, 'status_code', None),\n        }\n```\n\n**When to use:**\n- User asks to \"crawl a website\"\n- User wants to gather content from multiple pages\n- User needs to discover site structure\n\n### 2. Documentation Crawling\n\nSpecialized crawling for documentation sites with pattern filtering.\n\n```python\nfrom wrynai import WrynAI, Engine\n\ndef crawl_documentation(base_url: str, doc_patterns: list = None) -> list:\n    \"\"\"\n    Crawl documentation sites with targeted URL patterns.\n    \n    Args:\n        base_url: Base URL of the documentation site\n        doc_patterns: List of URL patterns to include (e.g., [\"\u002Fdocs\u002F\", \"\u002Fapi\u002F\"])\n    \n    Returns:\n        List of crawled documentation pages with content\n    \"\"\"\n    api_key = os.environ.get(\"WRYNAI_API_KEY\")\n    doc_patterns = doc_patterns or [\"\u002Fdocs\u002F\", \"\u002Fguide\u002F\", \"\u002Fapi\u002F\", \"\u002Freference\u002F\"]\n    \n    with WrynAI(api_key=api_key) as client:\n        result = client.crawl(\n            url=base_url,\n            max_pages=10,\n            max_depth=3,\n            include_patterns=doc_patterns,\n            exclude_patterns=[\"\u002Finternal\u002F\", \"\u002Fdraft\u002F\", \"\u002Fchangelog\u002F\", \"\u002Fadmin\u002F\"],\n            return_urls=True,\n            timeout_ms=60000,  # 60 seconds for documentation crawling\n        )\n        \n        return [\n            {\n                \"url\": page.page_url,\n                \"content\": page.content,\n                \"word_count\": len(page.content.split()),\n            }\n            for page in result.pages\n        ]\n```\n\n**When to use:**\n- User needs to extract documentation content\n- User wants to crawl specific sections of a site\n- User needs to build a knowledge base from docs\n\n### 3. Search + Crawl Pipeline\n\nSearch for topics and crawl the top results.\n\n```python\nfrom wrynai import WrynAI, CountryCode, WrynAIError\nimport time\n\ndef search_and_crawl(query: str, num_sites: int = 3, country: str = \"US\") -> list:\n    \"\"\"\n    Search for a query and crawl the top results.\n    \n    Args:\n        query: Search query\n        num_sites: Number of top results to crawl\n        country: Country code for search localization\n    \n    Returns:\n        List of search results with crawled content\n    \"\"\"\n    api_key = os.environ.get(\"WRYNAI_API_KEY\")\n    \n    with WrynAI(api_key=api_key) as client:\n        # Step 1: Perform search\n        try:\n            search_result = client.search(\n                query=query,\n                num_results=num_sites,\n                country_code=getattr(CountryCode, country, CountryCode.US),\n                timeout_ms=120000,\n            )\n        except WrynAIError as e:\n            return [{\"error\": f\"Search failed: {str(e)}\"}]\n        \n        # Step 2: Crawl each result\n        results = []\n        for result in search_result.organic_results[:num_sites]:\n            try:\n                crawl_result = client.crawl(\n                    url=result.url,\n                    max_pages=3,\n                    max_depth=1,\n                    timeout_ms=60000,\n                )\n                \n                results.append({\n                    \"search_position\": result.position,\n                    \"title\": result.title,\n                    \"url\": result.url,\n                    \"snippet\": result.snippet,\n                    \"crawled_pages\": [\n                        {\n                            \"url\": page.page_url,\n                            \"content_preview\": page.content[:500],\n                            \"full_content\": page.content,\n                        }\n                        for page in crawl_result.pages\n                    ],\n                })\n                \n                # Rate limiting courtesy\n                time.sleep(1)\n                \n            except WrynAIError as e:\n                results.append({\n                    \"title\": result.title,\n                    \"url\": result.url,\n                    \"error\": str(e),\n                })\n        \n        return results\n```\n\n**When to use:**\n- User wants to research a topic comprehensively\n- User needs content from top search results\n- User wants to compare information across multiple sources\n\n### 4. Content Extraction Only\n\nExtract specific content types without crawling.\n\n```python\nfrom wrynai import WrynAI, Engine\n\ndef extract_page_content(url: str, content_type: str = \"text\") -> dict:\n    \"\"\"\n    Extract specific content from a single page.\n    \n    Args:\n        url: Target URL\n        content_type: Type of content to extract \n                     (\"text\", \"markdown\", \"structured\", \"links\", \"title\")\n    \n    Returns:\n        Dictionary with extracted content\n    \"\"\"\n    api_key = os.environ.get(\"WRYNAI_API_KEY\")\n    \n    with WrynAI(api_key=api_key) as client:\n        try:\n            if content_type == \"text\":\n                result = client.extract_text(url, extract_main_content=True)\n                return {\"url\": url, \"text\": result.text}\n            \n            elif content_type == \"markdown\":\n                result = client.extract_markdown(url, extract_main_content=True)\n                return {\"url\": url, \"markdown\": result.markdown}\n            \n            elif content_type == \"structured\":\n                result = client.extract_structured_text(url)\n                return {\n                    \"url\": url,\n                    \"main_text\": result.main_text,\n                    \"headings\": [\n                        {\"level\": h.level, \"tag\": h.tag, \"text\": h.text}\n                        for h in result.headings\n                    ],\n                    \"links\": [\n                        {\"text\": l.text, \"url\": l.url, \"internal\": l.internal}\n                        for l in result.links\n                    ],\n                }\n            \n            elif content_type == \"links\":\n                result = client.extract_links(url)\n                return {\n                    \"url\": url,\n                    \"links\": [\n                        {\"text\": l.text, \"url\": l.url, \"internal\": l.internal}\n                        for l in result.links\n                    ],\n                }\n            \n            elif content_type == \"title\":\n                result = client.extract_title(url)\n                return {\"url\": url, \"title\": result.title}\n            \n            else:\n                return {\"error\": f\"Unknown content_type: {content_type}\"}\n                \n        except WrynAIError as e:\n            return {\"url\": url, \"error\": str(e)}\n```\n\n**When to use:**\n- User needs specific content from a single page\n- User wants structured data extraction\n- User needs to extract links or headings\n\n### 5. Robust Crawling with Error Handling\n\nProduction-ready crawling with retry logic and rate limit handling.\n\n```python\nfrom wrynai import WrynAI, RateLimitError, TimeoutError, ServerError, WrynAIError\nimport time\n\ndef robust_crawl(url: str, max_attempts: int = 3, max_pages: int = 10) -> dict:\n    \"\"\"\n    Crawl with automatic retry and error recovery.\n    \n    Args:\n        url: Starting URL\n        max_attempts: Maximum retry attempts\n        max_pages: Maximum pages to crawl\n    \n    Returns:\n        Crawl results with success status\n    \"\"\"\n    api_key = os.environ.get(\"WRYNAI_API_KEY\")\n    \n    with WrynAI(api_key=api_key, max_retries=3) as client:\n        for attempt in range(max_attempts):\n            try:\n                result = client.crawl(\n                    url=url,\n                    max_pages=max_pages,\n                    max_depth=3,\n                    timeout_ms=60000,\n                    retries=2,\n                )\n                \n                return {\n                    \"success\": True,\n                    \"attempt\": attempt + 1,\n                    \"total_visited\": result.total_visited,\n                    \"pages\": [\n                        {\n                            \"url\": page.page_url,\n                            \"content_length\": len(page.content),\n                            \"urls_found\": len(page.urls),\n                        }\n                        for page in result.pages\n                    ],\n                }\n            \n            except RateLimitError as e:\n                wait_time = e.retry_after or (2 ** attempt * 5)\n                print(f\"Rate limited. Waiting {wait_time}s before retry...\")\n                time.sleep(wait_time)\n                continue\n            \n            except TimeoutError:\n                print(f\"Timeout on attempt {attempt + 1}. Retrying...\")\n                continue\n            \n            except ServerError as e:\n                wait_time = 2 ** attempt\n                print(f\"Server error: {e}. Waiting {wait_time}s...\")\n                time.sleep(wait_time)\n                continue\n            \n            except WrynAIError as e:\n                return {\n                    \"success\": False,\n                    \"error\": str(e),\n                    \"error_type\": type(e).__name__,\n                    \"attempt\": attempt + 1,\n                }\n        \n        return {\n            \"success\": False,\n            \"error\": \"Maximum retry attempts exceeded\",\n            \"attempts\": max_attempts,\n        }\n```\n\n**When to use:**\n- Production environments requiring reliability\n- Crawling sites with rate limits\n- When dealing with potentially unstable targets\n\n### 6. JavaScript-Heavy Sites\n\nFor single-page applications and JavaScript-rendered content.\n\n```python\nfrom wrynai import WrynAI, Engine\n\ndef crawl_spa(url: str, max_pages: int = 5) -> dict:\n    \"\"\"\n    Crawl single-page applications or JavaScript-heavy sites.\n    \n    Args:\n        url: Starting URL\n        max_pages: Maximum pages to crawl\n    \n    Returns:\n        Crawl results with rendered content\n    \"\"\"\n    api_key = os.environ.get(\"WRYNAI_API_KEY\")\n    \n    with WrynAI(api_key=api_key) as client:\n        result = client.crawl(\n            url=url,\n            max_pages=max_pages,\n            max_depth=2,\n            engine=Engine.STEALTH_MODE,  # Use browser rendering\n            timeout_ms=90000,  # Longer timeout for JS rendering\n            return_urls=True,\n        )\n        \n        return {\n            \"success\": result.success,\n            \"total_visited\": result.total_visited,\n            \"pages\": [\n                {\n                    \"url\": page.page_url,\n                    \"content\": page.content,\n                    \"urls_found\": len(page.urls),\n                }\n                for page in result.pages\n            ],\n        }\n```\n\n**When to use:**\n- User needs to crawl React\u002FVue\u002FAngular applications\n- Content is dynamically loaded via JavaScript\n- Anti-bot protection is present\n\n## Key Parameters & Configuration\n\n### Crawl Limits\n\n```python\n# Hard limits enforced by the API\nMAX_PAGES = 10      # Maximum pages per crawl\nMAX_DEPTH = 3       # Maximum link depth\n```\n\n### Engine Selection\n\n```python\nEngine.SIMPLE         # Fast, for static HTML (default)\nEngine.STEALTH_MODE   # Slower, for JavaScript-rendered content\n```\n\n### Timeout Recommendations\n\n```python\n# Simple scraping: 30,000 ms (30 seconds)\n# Crawling: 60,000 ms (60 seconds) \n# Search operations: 120,000 ms (2 minutes)\n# Smart extraction: 45,000 ms (45 seconds)\n```\n\n### URL Pattern Filtering\n\n```python\n# Common patterns for include_patterns\nDOCS_PATTERNS = [\"\u002Fdocs\u002F\", \"\u002Fguide\u002F\", \"\u002Fapi\u002F\", \"\u002Freference\u002F\"]\nBLOG_PATTERNS = [\"\u002Fblog\u002F\", \"\u002Fposts\u002F\", \"\u002Farticles\u002F\"]\n\n# Common patterns for exclude_patterns\nEXCLUDE_PATTERNS = [\"\u002Fadmin\u002F\", \"\u002Flogin\u002F\", \"\u002Fdraft\u002F\", \"\u002Finternal\u002F\"]\nMEDIA_EXCLUDE = [\".pdf\", \".jpg\", \".png\", \".mp4\", \".zip\"]\n```\n\n## Error Handling\n\n### Exception Types\n\n```python\nfrom wrynai import (\n    WrynAIError,           # Base exception\n    AuthenticationError,    # Invalid API key (401)\n    BadRequestError,        # Invalid parameters (400)\n    RateLimitError,         # Rate limit exceeded (429)\n    TimeoutError,           # Request timeout\n    ServerError,            # Server error (5xx)\n    ConnectionError,        # Network issue\n    ValidationError,        # Local validation error\n)\n```\n\n### Error Handling Pattern\n\n```python\ntry:\n    result = client.crawl(url)\nexcept AuthenticationError:\n    # Check WRYNAI_API_KEY environment variable\n    pass\nexcept RateLimitError as e:\n    # Wait for e.retry_after seconds\n    time.sleep(e.retry_after or 60)\nexcept TimeoutError:\n    # Increase timeout_ms parameter\n    pass\nexcept WrynAIError as e:\n    # General API error\n    print(f\"Error: {e} (status: {e.status_code})\")\n```\n\n## Best Practices\n\n### 1. Always Use Environment Variables\n\n```python\nimport os\napi_key = os.environ.get(\"WRYNAI_API_KEY\")\nif not api_key:\n    raise ValueError(\"WRYNAI_API_KEY environment variable required\")\n```\n\n### 2. Use Context Managers\n\n```python\n# Recommended - automatic resource cleanup\nwith WrynAI(api_key=api_key) as client:\n    result = client.crawl(url)\n\n# Not recommended - manual cleanup required\nclient = WrynAI(api_key=api_key)\ntry:\n    result = client.crawl(url)\nfinally:\n    client.close()\n```\n\n### 3. Set Appropriate Timeouts\n\n```python\n# For simple pages\ntimeout_ms=30000\n\n# For crawling multiple pages\ntimeout_ms=60000\n\n# For JavaScript-heavy sites\ntimeout_ms=90000\n```\n\n### 4. Graceful Degradation\n\n```python\ntry:\n    # Try structured extraction first\n    result = client.extract_structured_text(url)\n    content = result.main_text\nexcept Exception:\n    try:\n        # Fall back to simple text\n        result = client.extract_text(url)\n        content = result.text\n    except Exception:\n        content = None\n```\n\n### 5. Respect Rate Limits\n\n```python\nimport time\n\nfor url in urls:\n    result = client.crawl(url)\n    time.sleep(1)  # Be nice to the API\n```\n\n## Advanced Features\n\n### Smart Listing Extraction (PRO)\n\nExtract structured data from listing pages (e-commerce, directories).\n\n```python\ndef extract_product_listings(url: str) -> list:\n    \"\"\"Extract product information from listing pages.\"\"\"\n    api_key = os.environ.get(\"WRYNAI_API_KEY\")\n    \n    with WrynAI(api_key=api_key) as client:\n        result = client.auto_listing(\n            url=url,\n            engine=Engine.STEALTH_MODE,\n            timeout_ms=60000,\n        )\n        \n        return [\n            {\n                \"title\": item.get(\"title\"),\n                \"price\": item.get(\"price\"),\n                \"rating\": item.get(\"rating\"),\n                \"url\": item.get(\"url\"),\n            }\n            for item in result.items\n        ]\n```\n\n### Screenshot Capture\n\n```python\nimport base64\nfrom wrynai import ScreenshotType\n\ndef capture_page_screenshot(url: str, fullpage: bool = False) -> str:\n    \"\"\"Capture page screenshot and save to file.\"\"\"\n    api_key = os.environ.get(\"WRYNAI_API_KEY\")\n    \n    with WrynAI(api_key=api_key) as client:\n        result = client.take_screenshot(\n            url=url,\n            screenshot_type=ScreenshotType.FULLPAGE if fullpage else ScreenshotType.VIEWPORT,\n            timeout_ms=30000,\n        )\n        \n        # Decode and save\n        image_data = result.screenshot\n        if \",\" in image_data:\n            image_data = image_data.split(\",\")[1]\n        \n        filename = \"screenshot.png\"\n        with open(filename, \"wb\") as f:\n            f.write(base64.b64decode(image_data))\n        \n        return filename\n```\n\n## Common Use Cases\n\n### 1. Competitive Research\n\"Search for [topic] and crawl the top 5 results\"\n\n### 2. Documentation Aggregation\n\"Crawl the Python documentation and extract all API references\"\n\n### 3. Content Migration\n\"Crawl our old website and extract all blog posts in markdown\"\n\n### 4. Link Analysis\n\"Find all external links on [website]\"\n\n### 5. Site Monitoring\n\"Crawl [site] and check if [content] is present\"\n\n### 6. Knowledge Base Creation\n\"Crawl [documentation site] and create a searchable knowledge base\"\n\n## Limitations & Considerations\n\n1. **Hard Limits**: Maximum 10 pages per crawl, depth of 3\n2. **Rate Limits**: API has rate limits; handle `RateLimitError` appropriately\n3. **Timeout Management**: Adjust timeouts based on site complexity\n4. **JavaScript Rendering**: Use `Engine.STEALTH_MODE` for SPAs (slower but necessary)\n5. **Robots.txt**: SDK respects robots.txt; some pages may be blocked\n6. **Dynamic Content**: Some dynamically loaded content may require stealth mode\n\n## Troubleshooting\n\n### Common Issues\n\n**Issue**: `AuthenticationError`\n- **Solution**: Verify `WRYNAI_API_KEY` environment variable is set correctly\n\n**Issue**: `RateLimitError`\n- **Solution**: Implement retry with `e.retry_after` wait time\n\n**Issue**: `TimeoutError`\n- **Solution**: Increase `timeout_ms` parameter\n\n**Issue**: Empty content returned\n- **Solution**: Try `Engine.STEALTH_MODE` for JavaScript-rendered pages\n\n**Issue**: Missing links\u002Fcontent\n- **Solution**: Check `exclude_patterns` and `include_patterns` configuration\n\n## Integration with OpenClaw\n\nWhen using this skill with OpenClaw:\n\n1. **Set environment variable** before running:\n   ```bash\n   export WRYNAI_API_KEY=\"your-api-key\"\n   ```\n\n2. **Install dependencies**:\n   ```bash\n   pip install wrynai\n   ```\n\n3. **Use in your OpenClaw workflows**:\n   - Call the crawling functions directly from your automation scripts\n   - Integrate with other OpenClaw skills for comprehensive data pipelines\n   - Use the returned data structures in downstream processing\n\n## API Reference Quick Links\n\n- Documentation: https:\u002F\u002Fdocs.wryn.ai\n- API Signup: https:\u002F\u002Fwryn.ai\n- GitHub: https:\u002F\u002Fgithub.com\u002Fwrynai\u002Fwrynai-python\n\n## Version Information\n\n- **Skill Version**: 1.0.0\n- **SDK Version**: wrynai v1.0.0\n- **Python Version**: 3.8+\n- **Last Updated**: 2025-02-07",{},"main","e7e336ac628c3e3bd771aff1aaa469c93778f94a","skills\u002Fwrynai\u002Fwrynai-skill",0,"https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del","2026-08-23 22:39:37",{"source":7,"skillName":5,"commands":35,"prompt":45,"zipAvailable":46},[36,39,42],{"tool":37,"command":38},"npx","npx skills add kbarbel640-del\u002Fskills --skill wrynai-skill",{"tool":40,"command":41},"bunx","bunx skills add kbarbel640-del\u002Fskills --skill wrynai-skill",{"tool":43,"command":44},"pnpm","pnpm dlx skills add kbarbel640-del\u002Fskills --skill wrynai-skill","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fwrynai\u002Fwrynai-skill\u002FSKILL.MD",true,[48],{"path":49,"resourceType":50,"resourceTypeDesc":51,"sizeBytes":52,"sourceHtmlUrl":53},"_meta.json","REFERENCE","参考文档",276,"https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fwrynai\u002Fwrynai-skill\u002F_meta.json",[55,86,111,132,138,158],{"skillNo":56,"name":57,"nameZh":6,"description":58,"descriptionZh":6,"repositoryFullName":7,"ownerLogin":8,"ownerAvatarUrl":9,"ownerAccountNo":10,"ownerDisplayName":6,"repositoryNo":11,"starsCount":12,"licenseSpdxId":13,"licenseFileUrl":6,"sourceHtmlUrl":59,"categories":60,"keywords":66,"publishedAt":23},"01M6G8J55967D6281ACMKAKTEQ","crowd-prompting","A marketplace where AI agents improve prompts, system instructions, tool descriptions, and other text-based content with domain expertise from real-world operations — and earn tokens for valuable contributions.","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fzzadrian\u002Fcrowd-prompting\u002FSKILL.md",[61],{"categoryNo":62,"categoryName":63,"taxonomyType":64,"taxonomyTypeDesc":65},"01JBSEEDCAT000000000000036","内容创作者","PROFESSION","适用职业",[67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85],"crowd prompting","prompting","api","with","tokens","domain","world","prompts","operations","instructions","text","tool","system","improve","productivity","marketplace","https","content","ai agents",{"skillNo":87,"name":88,"nameZh":6,"description":89,"descriptionZh":6,"repositoryFullName":7,"ownerLogin":8,"ownerAvatarUrl":9,"ownerAccountNo":10,"ownerDisplayName":6,"repositoryNo":11,"starsCount":12,"licenseSpdxId":13,"licenseFileUrl":6,"sourceHtmlUrl":90,"categories":91,"keywords":93,"publishedAt":23},"01M6G8J0PKPAYVET6BWE8W4C26","dilemm-ai","Compete in DilemmAI, the prisoner's dilemma AI arena at dilemm.ai. Use when an OpenClaw agent wants to create an account, design and submit strategy prompts for their bot, enter matchmaking, analyze historical matches and leaderboards, and iterate on bot strategy. Requires headless browser automation (no API available yet).","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fzyori\u002Fdilemm-ai\u002FSKILL.md",[92],{"categoryNo":17,"categoryName":18,"taxonomyType":19,"taxonomyTypeDesc":20},[94,69,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,74,110],"dilemm ai","arena","analyze","browser","openclaw agent","create","automation","browser automation","bot","openclaw","design","strategy","headless","compete","submit","matchmaking","use",{"skillNo":112,"name":113,"nameZh":6,"description":114,"descriptionZh":6,"repositoryFullName":7,"ownerLogin":8,"ownerAvatarUrl":9,"ownerAccountNo":10,"ownerDisplayName":6,"repositoryNo":11,"starsCount":12,"licenseSpdxId":13,"licenseFileUrl":6,"sourceHtmlUrl":115,"categories":116,"keywords":120,"publishedAt":23},"01M6G8HWAF3K9SW7NP3Z83CPJ6","arxiv-paper-reviews","Interact with arXiv Crawler API to fetch papers, read reviews, and submit comments. Use when working with arXiv papers, fetching paper lists by date\u002Fcategory\u002Finterest, viewing paper details with comments, or submitting paper reviews via API at http:\u002F\u002F150.158.152.82:8000.","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fzxrys\u002Fweak-accept\u002FSKILL.md",[117],{"categoryNo":118,"categoryName":119,"taxonomyType":19,"taxonomyTypeDesc":20},"01JBSEEDCAT000000000000021","资料检索与研究",[121,122,123,124,125,126,127,70,128,108,110,129,69,130,131],"arxiv paper reviews","reviews","arxiv","paper","crawler","papers","comments","fetch","read","http","via",{"skillNo":133,"name":113,"nameZh":6,"description":114,"descriptionZh":6,"repositoryFullName":7,"ownerLogin":8,"ownerAvatarUrl":9,"ownerAccountNo":10,"ownerDisplayName":6,"repositoryNo":11,"starsCount":12,"licenseSpdxId":13,"licenseFileUrl":6,"sourceHtmlUrl":134,"categories":135,"keywords":137,"publishedAt":23},"01M6G8HQJ7N7WMY6YV7D7SSJ16","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fzxrys\u002Farxiv-paper-reviews\u002FSKILL.md",[136],{"categoryNo":118,"categoryName":119,"taxonomyType":19,"taxonomyTypeDesc":20},[124,123,122,121,131,126,127,70,125,108,110,128,129,69,130],{"skillNo":139,"name":140,"nameZh":6,"description":141,"descriptionZh":6,"repositoryFullName":7,"ownerLogin":8,"ownerAvatarUrl":9,"ownerAccountNo":10,"ownerDisplayName":6,"repositoryNo":11,"starsCount":12,"licenseSpdxId":13,"licenseFileUrl":6,"sourceHtmlUrl":142,"categories":143,"keywords":144,"publishedAt":23},"01M6G8HM95Y64JNVFC2HN4E2BG","git-summary","Get a quick summary of the current Git repository including status, recent commits, branches, and contributors.","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fzweack\u002Fgit-summary\u002FSKILL.md",[],[145,146,147,148,149,150,151,152,153,154,155,156,157],"git","summary","git summary","commits","repository","win32","status","linux","contributors","true","quick","get","branches",{"skillNo":159,"name":160,"nameZh":6,"description":161,"descriptionZh":6,"repositoryFullName":7,"ownerLogin":8,"ownerAvatarUrl":9,"ownerAccountNo":10,"ownerDisplayName":6,"repositoryNo":11,"starsCount":12,"licenseSpdxId":13,"licenseFileUrl":6,"sourceHtmlUrl":162,"categories":163,"keywords":168,"publishedAt":23},"01M6G8HGEGF05CNEJCGVYFSC4R","agent-constitution","Interact with AgentConstitution governance contracts on Base Sepolia. Check compliance, read rules, log actions, query governance state.","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fztsalexey\u002Fagent-constitution\u002FSKILL.md",[164,165],{"categoryNo":17,"categoryName":18,"taxonomyType":19,"taxonomyTypeDesc":20},{"categoryNo":166,"categoryName":167,"taxonomyType":64,"taxonomyTypeDesc":65},"01JBSEEDCAT000000000000037","律师与法务",[169,170,171,172,70,173,174,27,175,129,176,177,178,179,180,83,181,182,183],"agent constitution","constitution","contracts","tree","query","base","log","check","Rules","projects","compliance","actions","state","governance","github"]