[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6XEPZ3AY7GP2AXD4C737N5Z":3,"skill-same:01M6XEPZ3AY7GP2AXD4C737N5Z":64},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":9,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":15,"categories":16,"keywords":17,"publishedAt":38,"linkOnly":39,"markdownContent":40,"markdownBody":41,"frontMatter":42,"refName":43,"commitSha":44,"skillDirectory":45,"forksCount":13,"repositoryHtmlUrl":46,"repositoryHomepageUrl":6,"ownerHtmlUrl":47,"ownerBlogUrl":6,"ownerDescription":48,"updatedAt":49,"install":50,"resources":63},"01M6XEPZ3AY7GP2AXD4C737N5Z","trivy-offline-vulnerability-scanning",null,"Use Trivy vulnerability scanner in offline mode to discover security vulnerabilities in dependency files. This skill covers setting up offline scanning, executing Trivy against package lock files, and generating JSON vulnerability reports without requiring internet access.","Waaaalnut\u002Fskillsbench","Waaaalnut","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F103995656?v=4","01M6XCS9K1V51EY3JMB7DGMX24","01M6XCS9Q4WPW88W62C55G1H44",0,"Apache-2.0","https:\u002F\u002Fgithub.com\u002FWaaaalnut\u002Fskillsbench\u002Fblob\u002Fmain\u002Ftasks\u002Fsoftware-dependency-audit\u002Fenvironment\u002Fskills\u002Ftrivy-offline-vulnerability-scanning\u002FSKILL.md",[],[18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37],"vulnerability scanning","trivy offline vulnerability scanning","scanning","vulnerability","trivy","offline","vulnerability scanner","access","package","dependency","up","reports","files","scanner","discover","Trivy Vulnerability Scanner","internet","mode","lock","security","2026-11-10 10:12:30",false,"---\nname: trivy-offline-vulnerability-scanning\ndescription: Use Trivy vulnerability scanner in offline mode to discover security vulnerabilities in dependency files. This skill covers setting up offline scanning, executing Trivy against package lock files, and generating JSON vulnerability reports without requiring internet access.\n---\n\n# Trivy Offline Vulnerability Scanning\n\nThis skill provides guidance on using Trivy, an open-source security scanner, to discover vulnerabilities in software dependencies using offline mode.\n\n## Overview\n\nTrivy is a comprehensive vulnerability scanner that can analyze various targets including container images, filesystems, and dependency lock files. **Offline scanning** is crucial for:\n- Air-gapped environments without internet access\n- Reproducible security audits with fixed vulnerability databases\n- Faster CI\u002FCD pipelines avoiding network latency\n- Compliance requirements for controlled environments\n\n## Why Offline Mode?\n\n### Challenges with Online Scanning\n- Network dependency introduces failure points\n- Database updates can cause inconsistent results across runs\n- Slower execution due to download times\n- Security policies may restrict external connections\n\n### Benefits of Offline Scanning\n- **Reproducibility**: Same database = same results\n- **Speed**: No network overhead\n- **Reliability**: No external dependencies\n- **Compliance**: Works in restricted environments\n\n## Trivy Database Structure\n\nTrivy's vulnerability database consists of:\n- **trivy.db**: SQLite database containing CVE information\n- **metadata.json**: Database version and update timestamp\n\nDatabase location: `\u003Ccache-dir>\u002Fdb\u002Ftrivy.db`\n\n## Offline Scanning Workflow\n\n### Step 1: Verify Database Existence\n\nBefore scanning, ensure the offline database is available:\n\n```python\nimport os\nimport sys\n\nTRIVY_CACHE_PATH = '.\u002Ftrivy-cache'\n\n# Check for database file\ndb_path = os.path.join(TRIVY_CACHE_PATH, \"db\", \"trivy.db\")\nif not os.path.exists(db_path):\n    print(f\"[!] Error: Trivy database not found at {db_path}\")\n    print(\"    Download database first with:\")\n    print(f\"    trivy image --download-db-only --cache-dir {TRIVY_CACHE_PATH}\")\n    sys.exit(1)\n```\n\n### Step 2: Construct Trivy Command\n\nKey flags for offline scanning:\n\n| Flag | Purpose |\n|------|---------|\n| `fs \u003Ctarget>` | Scan filesystem\u002Ffile (e.g., package-lock.json) |\n| `--format json` | Output in JSON format for parsing |\n| `--output \u003Cfile>` | Save results to file |\n| `--scanners vuln` | Scan only for vulnerabilities (not misconfigs) |\n| `--skip-db-update` | **Critical**: Do not update database |\n| `--offline-scan` | Enable offline mode |\n| `--cache-dir \u003Cpath>` | Path to pre-downloaded database |\n\n```python\nimport subprocess\n\nTARGET_FILE = 'package-lock.json'\nOUTPUT_FILE = 'trivy_report.json'\nTRIVY_CACHE_PATH = '.\u002Ftrivy-cache'\n\ncommand = [\n    \"trivy\", \"fs\", TARGET_FILE,\n    \"--format\", \"json\",\n    \"--output\", OUTPUT_FILE,\n    \"--scanners\", \"vuln\",\n    \"--skip-db-update\",      # Prevent online updates\n    \"--offline-scan\",         # Enable offline mode\n    \"--cache-dir\", TRIVY_CACHE_PATH\n]\n```\n\n### Step 3: Execute Scan\n\n```python\ntry:\n    result = subprocess.run(\n        command,\n        capture_output=True,\n        text=True,\n        check=False  # Don't raise exception on non-zero exit\n    )\n    \n    if result.returncode != 0:\n        print(\"[!] Trivy scan failed:\")\n        print(result.stderr)\n        sys.exit(1)\n    \n    print(\"[*] Scan completed successfully\")\n    print(f\"[*] Results saved to: {OUTPUT_FILE}\")\n    \nexcept FileNotFoundError:\n    print(\"[!] Error: 'trivy' command not found\")\n    print(\"    Install Trivy: https:\u002F\u002Faquasecurity.github.io\u002Ftrivy\u002Flatest\u002Fgetting-started\u002Finstallation\u002F\")\n    sys.exit(1)\n```\n\n## Complete Example\n\n```python\nimport os\nimport sys\nimport subprocess\n\ndef run_trivy_offline_scan(target_file, output_file, cache_dir='.\u002Ftrivy-cache'):\n    \"\"\"\n    Execute Trivy vulnerability scan in offline mode.\n    \n    Args:\n        target_file: Path to file to scan (e.g., package-lock.json)\n        output_file: Path to save JSON results\n        cache_dir: Path to Trivy offline database\n    \"\"\"\n    print(f\"[*] Starting Trivy offline scan...\")\n    print(f\"    Target: {target_file}\")\n    print(f\"    Database: {cache_dir}\")\n    \n    # Verify database exists\n    db_path = os.path.join(cache_dir, \"db\", \"trivy.db\")\n    if not os.path.exists(db_path):\n        print(f\"[!] Error: Database not found at {db_path}\")\n        sys.exit(1)\n    \n    # Build command\n    command = [\n        \"trivy\", \"fs\", target_file,\n        \"--format\", \"json\",\n        \"--output\", output_file,\n        \"--scanners\", \"vuln\",\n        \"--skip-db-update\",\n        \"--offline-scan\",\n        \"--cache-dir\", cache_dir\n    ]\n    \n    # Execute\n    try:\n        result = subprocess.run(command, capture_output=True, text=True)\n        \n        if result.returncode != 0:\n            print(\"[!] Scan failed:\")\n            print(result.stderr)\n            sys.exit(1)\n        \n        print(\"[*] Scan completed successfully\")\n        return output_file\n        \n    except FileNotFoundError:\n        print(\"[!] Trivy not found. Install from:\")\n        print(\"    https:\u002F\u002Faquasecurity.github.io\u002Ftrivy\u002F\")\n        sys.exit(1)\n\n# Usage\nif __name__ == \"__main__\":\n    run_trivy_offline_scan(\n        target_file='package-lock.json',\n        output_file='trivy_report.json'\n    )\n```\n\n## JSON Output Structure\n\nTrivy outputs vulnerability data in this format:\n\n```json\n{\n  \"Results\": [\n    {\n      \"Target\": \"package-lock.json\",\n      \"Vulnerabilities\": [\n        {\n          \"VulnerabilityID\": \"CVE-2021-44906\",\n          \"PkgName\": \"minimist\",\n          \"InstalledVersion\": \"1.2.5\",\n          \"FixedVersion\": \"1.2.6\",\n          \"Severity\": \"CRITICAL\",\n          \"Title\": \"Prototype Pollution in minimist\",\n          \"PrimaryURL\": \"https:\u002F\u002Favd.aquasec.com\u002Fnvd\u002Fcve-2021-44906\",\n          \"CVSS\": {\n            \"nvd\": { \"V3Score\": 9.8 }\n          }\n        }\n      ]\n    }\n  ]\n}\n```\n\n## Common Issues\n\n### Issue: \"failed to initialize DB\"\n**Cause**: Database not found or corrupted  \n**Solution**: Re-download database or check `--cache-dir` path\n\n### Issue: Scan finds no vulnerabilities when they exist\n**Cause**: Database is outdated  \n**Solution**: Download newer database (before going offline)\n\n### Issue: \"command not found: trivy\"\n**Cause**: Trivy not installed or not in PATH  \n**Solution**: Install Trivy following official documentation\n\n## Dependencies\n\n### Required Tools\n- **Trivy**: Version 0.40.0 or later recommended\n  ```bash\n  # Installation (example for Debian\u002FUbuntu)\n  wget -qO - https:\u002F\u002Faquasecurity.github.io\u002Ftrivy-repo\u002Fdeb\u002Fpublic.key | apt-key add -\n  echo \"deb https:\u002F\u002Faquasecurity.github.io\u002Ftrivy-repo\u002Fdeb $(lsb_release -sc) main\" | tee -a \u002Fetc\u002Fapt\u002Fsources.list.d\u002Ftrivy.list\n  apt-get update\n  apt-get install trivy\n  ```\n\n### Python Modules\n- `subprocess` (standard library)\n- `os` (standard library)\n- `sys` (standard library)\n\n## References\n\n- [Trivy Documentation](https:\u002F\u002Faquasecurity.github.io\u002Ftrivy\u002F)\n- [Trivy Offline Mode Guide](https:\u002F\u002Faquasecurity.github.io\u002Ftrivy\u002Flatest\u002Fdocs\u002Fadvanced\u002Fair-gap\u002F)\n- [CVE Database](https:\u002F\u002Fcve.mitre.org\u002F)\n","# Trivy Offline Vulnerability Scanning\n\nThis skill provides guidance on using Trivy, an open-source security scanner, to discover vulnerabilities in software dependencies using offline mode.\n\n## Overview\n\nTrivy is a comprehensive vulnerability scanner that can analyze various targets including container images, filesystems, and dependency lock files. **Offline scanning** is crucial for:\n- Air-gapped environments without internet access\n- Reproducible security audits with fixed vulnerability databases\n- Faster CI\u002FCD pipelines avoiding network latency\n- Compliance requirements for controlled environments\n\n## Why Offline Mode?\n\n### Challenges with Online Scanning\n- Network dependency introduces failure points\n- Database updates can cause inconsistent results across runs\n- Slower execution due to download times\n- Security policies may restrict external connections\n\n### Benefits of Offline Scanning\n- **Reproducibility**: Same database = same results\n- **Speed**: No network overhead\n- **Reliability**: No external dependencies\n- **Compliance**: Works in restricted environments\n\n## Trivy Database Structure\n\nTrivy's vulnerability database consists of:\n- **trivy.db**: SQLite database containing CVE information\n- **metadata.json**: Database version and update timestamp\n\nDatabase location: `\u003Ccache-dir>\u002Fdb\u002Ftrivy.db`\n\n## Offline Scanning Workflow\n\n### Step 1: Verify Database Existence\n\nBefore scanning, ensure the offline database is available:\n\n```python\nimport os\nimport sys\n\nTRIVY_CACHE_PATH = '.\u002Ftrivy-cache'\n\n# Check for database file\ndb_path = os.path.join(TRIVY_CACHE_PATH, \"db\", \"trivy.db\")\nif not os.path.exists(db_path):\n    print(f\"[!] Error: Trivy database not found at {db_path}\")\n    print(\"    Download database first with:\")\n    print(f\"    trivy image --download-db-only --cache-dir {TRIVY_CACHE_PATH}\")\n    sys.exit(1)\n```\n\n### Step 2: Construct Trivy Command\n\nKey flags for offline scanning:\n\n| Flag | Purpose |\n|------|---------|\n| `fs \u003Ctarget>` | Scan filesystem\u002Ffile (e.g., package-lock.json) |\n| `--format json` | Output in JSON format for parsing |\n| `--output \u003Cfile>` | Save results to file |\n| `--scanners vuln` | Scan only for vulnerabilities (not misconfigs) |\n| `--skip-db-update` | **Critical**: Do not update database |\n| `--offline-scan` | Enable offline mode |\n| `--cache-dir \u003Cpath>` | Path to pre-downloaded database |\n\n```python\nimport subprocess\n\nTARGET_FILE = 'package-lock.json'\nOUTPUT_FILE = 'trivy_report.json'\nTRIVY_CACHE_PATH = '.\u002Ftrivy-cache'\n\ncommand = [\n    \"trivy\", \"fs\", TARGET_FILE,\n    \"--format\", \"json\",\n    \"--output\", OUTPUT_FILE,\n    \"--scanners\", \"vuln\",\n    \"--skip-db-update\",      # Prevent online updates\n    \"--offline-scan\",         # Enable offline mode\n    \"--cache-dir\", TRIVY_CACHE_PATH\n]\n```\n\n### Step 3: Execute Scan\n\n```python\ntry:\n    result = subprocess.run(\n        command,\n        capture_output=True,\n        text=True,\n        check=False  # Don't raise exception on non-zero exit\n    )\n    \n    if result.returncode != 0:\n        print(\"[!] Trivy scan failed:\")\n        print(result.stderr)\n        sys.exit(1)\n    \n    print(\"[*] Scan completed successfully\")\n    print(f\"[*] Results saved to: {OUTPUT_FILE}\")\n    \nexcept FileNotFoundError:\n    print(\"[!] Error: 'trivy' command not found\")\n    print(\"    Install Trivy: https:\u002F\u002Faquasecurity.github.io\u002Ftrivy\u002Flatest\u002Fgetting-started\u002Finstallation\u002F\")\n    sys.exit(1)\n```\n\n## Complete Example\n\n```python\nimport os\nimport sys\nimport subprocess\n\ndef run_trivy_offline_scan(target_file, output_file, cache_dir='.\u002Ftrivy-cache'):\n    \"\"\"\n    Execute Trivy vulnerability scan in offline mode.\n    \n    Args:\n        target_file: Path to file to scan (e.g., package-lock.json)\n        output_file: Path to save JSON results\n        cache_dir: Path to Trivy offline database\n    \"\"\"\n    print(f\"[*] Starting Trivy offline scan...\")\n    print(f\"    Target: {target_file}\")\n    print(f\"    Database: {cache_dir}\")\n    \n    # Verify database exists\n    db_path = os.path.join(cache_dir, \"db\", \"trivy.db\")\n    if not os.path.exists(db_path):\n        print(f\"[!] Error: Database not found at {db_path}\")\n        sys.exit(1)\n    \n    # Build command\n    command = [\n        \"trivy\", \"fs\", target_file,\n        \"--format\", \"json\",\n        \"--output\", output_file,\n        \"--scanners\", \"vuln\",\n        \"--skip-db-update\",\n        \"--offline-scan\",\n        \"--cache-dir\", cache_dir\n    ]\n    \n    # Execute\n    try:\n        result = subprocess.run(command, capture_output=True, text=True)\n        \n        if result.returncode != 0:\n            print(\"[!] Scan failed:\")\n            print(result.stderr)\n            sys.exit(1)\n        \n        print(\"[*] Scan completed successfully\")\n        return output_file\n        \n    except FileNotFoundError:\n        print(\"[!] Trivy not found. Install from:\")\n        print(\"    https:\u002F\u002Faquasecurity.github.io\u002Ftrivy\u002F\")\n        sys.exit(1)\n\n# Usage\nif __name__ == \"__main__\":\n    run_trivy_offline_scan(\n        target_file='package-lock.json',\n        output_file='trivy_report.json'\n    )\n```\n\n## JSON Output Structure\n\nTrivy outputs vulnerability data in this format:\n\n```json\n{\n  \"Results\": [\n    {\n      \"Target\": \"package-lock.json\",\n      \"Vulnerabilities\": [\n        {\n          \"VulnerabilityID\": \"CVE-2021-44906\",\n          \"PkgName\": \"minimist\",\n          \"InstalledVersion\": \"1.2.5\",\n          \"FixedVersion\": \"1.2.6\",\n          \"Severity\": \"CRITICAL\",\n          \"Title\": \"Prototype Pollution in minimist\",\n          \"PrimaryURL\": \"https:\u002F\u002Favd.aquasec.com\u002Fnvd\u002Fcve-2021-44906\",\n          \"CVSS\": {\n            \"nvd\": { \"V3Score\": 9.8 }\n          }\n        }\n      ]\n    }\n  ]\n}\n```\n\n## Common Issues\n\n### Issue: \"failed to initialize DB\"\n**Cause**: Database not found or corrupted  \n**Solution**: Re-download database or check `--cache-dir` path\n\n### Issue: Scan finds no vulnerabilities when they exist\n**Cause**: Database is outdated  \n**Solution**: Download newer database (before going offline)\n\n### Issue: \"command not found: trivy\"\n**Cause**: Trivy not installed or not in PATH  \n**Solution**: Install Trivy following official documentation\n\n## Dependencies\n\n### Required Tools\n- **Trivy**: Version 0.40.0 or later recommended\n  ```bash\n  # Installation (example for Debian\u002FUbuntu)\n  wget -qO - https:\u002F\u002Faquasecurity.github.io\u002Ftrivy-repo\u002Fdeb\u002Fpublic.key | apt-key add -\n  echo \"deb https:\u002F\u002Faquasecurity.github.io\u002Ftrivy-repo\u002Fdeb $(lsb_release -sc) main\" | tee -a \u002Fetc\u002Fapt\u002Fsources.list.d\u002Ftrivy.list\n  apt-get update\n  apt-get install trivy\n  ```\n\n### Python Modules\n- `subprocess` (standard library)\n- `os` (standard library)\n- `sys` (standard library)\n\n## References\n\n- [Trivy Documentation](https:\u002F\u002Faquasecurity.github.io\u002Ftrivy\u002F)\n- [Trivy Offline Mode Guide](https:\u002F\u002Faquasecurity.github.io\u002Ftrivy\u002Flatest\u002Fdocs\u002Fadvanced\u002Fair-gap\u002F)\n- [CVE Database](https:\u002F\u002Fcve.mitre.org\u002F)\n",{"name":5,"description":7},"main","7eeb258ada72b7f58119b0e7a2c00ea89d9beedd","tasks\u002Fsoftware-dependency-audit\u002Fenvironment\u002Fskills\u002Ftrivy-offline-vulnerability-scanning","https:\u002F\u002Fgithub.com\u002FWaaaalnut\u002Fskillsbench","https:\u002F\u002Fgithub.com\u002FWaaaalnut","student of Zhejiang University","2026-04-21 23:16:23",{"source":8,"skillName":5,"commands":51,"prompt":61,"zipAvailable":62},[52,55,58],{"tool":53,"command":54},"npx","npx skills add Waaaalnut\u002Fskillsbench --skill trivy-offline-vulnerability-scanning",{"tool":56,"command":57},"bunx","bunx skills add Waaaalnut\u002Fskillsbench --skill trivy-offline-vulnerability-scanning",{"tool":59,"command":60},"pnpm","pnpm dlx skills add Waaaalnut\u002Fskillsbench --skill trivy-offline-vulnerability-scanning","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FWaaaalnut\u002Fskillsbench\u002Fblob\u002Fmain\u002Ftasks\u002Fsoftware-dependency-audit\u002Fenvironment\u002Fskills\u002Ftrivy-offline-vulnerability-scanning\u002FSKILL.md",true,[],[65,79,94,122,144,163],{"skillNo":66,"name":67,"nameZh":6,"description":6,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":9,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":68,"categories":69,"keywords":75,"publishedAt":38},"01M6XEWMJ6VY3ZC53MPDCPG3GH","data-reconciliation","https:\u002F\u002Fgithub.com\u002FWaaaalnut\u002Fskillsbench\u002Fblob\u002Fmain\u002Ftasks\u002Fxlsx-recover-data\u002Fenvironment\u002Fskills\u002Fdata-reconciliation\u002FSKILL.md",[70],{"categoryNo":71,"categoryName":72,"taxonomyType":73,"taxonomyTypeDesc":74},"01JBSEEDCAT000000000000033","数据分析师","PROFESSION","适用职业",[76,77,78],"data reconciliation","reconciliation","data",{"skillNo":80,"name":81,"nameZh":6,"description":82,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":9,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":83,"categories":84,"keywords":85,"publishedAt":38},"01M6XEW8MNPMF1KRXV6ATGFRQF","speech-to-text","Transcribe video to timestamped text using Whisper tiny model (pre-installed).","https:\u002F\u002Fgithub.com\u002FWaaaalnut\u002Fskillsbench\u002Fblob\u002Fmain\u002Ftasks\u002Fvideo-tutorial-indexer\u002Fenvironment\u002Fskills\u002Fspeech-to-text\u002FSKILL.md",[],[86,87,88,89,90,91,92,93],"speech","text","speech to text","transcribe video","whisper","model","Video","transcribe",{"skillNo":95,"name":96,"nameZh":6,"description":97,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":9,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":98,"categories":99,"keywords":105,"publishedAt":38},"01M6XEW3FQZP0T1RKQQJFXVY9T","video-processor","Process videos by removing segments and concatenating remaining parts. Use when you need to remove detected pauses\u002Fopenings from videos, create highlight reels, or batch process segment removals using ffmpeg filter_complex.","https:\u002F\u002Fgithub.com\u002FWaaaalnut\u002Fskillsbench\u002Fblob\u002Fmain\u002Ftasks\u002Fvideo-silence-remover\u002Fenvironment\u002Fskills\u002Fvideo-processor\u002FSKILL.md",[100],{"categoryNo":101,"categoryName":102,"taxonomyType":103,"taxonomyTypeDesc":104},"01JBSEEDCAT000000000000016","图像与多媒体","SCENARIO","使用场景",[92,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121],"processor","video processor","batch","create","reels","when","parts","segments","process","videos","you","segment","filter","ffmpeg","use","remove",{"skillNo":123,"name":124,"nameZh":6,"description":125,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":9,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":126,"categories":127,"keywords":129,"publishedAt":38},"01M6XEVXJ5KZ0NTY3XZKRY4AS1","silence-detector","Detect initial silence segments in audio\u002Fvideo using energy-based analysis. Use when you need to find low-energy periods at the start of recordings (title slides, setup time, pre-roll silence).","https:\u002F\u002Fgithub.com\u002FWaaaalnut\u002Fskillsbench\u002Fblob\u002Fmain\u002Ftasks\u002Fvideo-silence-remover\u002Fenvironment\u002Fskills\u002Fsilence-detector\u002FSKILL.md",[128],{"categoryNo":101,"categoryName":102,"taxonomyType":103,"taxonomyTypeDesc":104},[130,131,132,133,111,116,134,135,136,137,138,113,139,140,92,141,142,143,120],"detector","silence detector","title","slides","time","energy","at","recordings","detect","find","Audio","analysis","start","setup",{"skillNo":145,"name":146,"nameZh":6,"description":147,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":9,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":148,"categories":149,"keywords":150,"publishedAt":38},"01M6XEVT3NGRN1FT7JPMAPXS6M","segment-combiner","Combine multiple segment detection results into a unified list. Use when you need to merge segments from different detectors, prepare removal lists for video processing, or consolidate detection outputs.","https:\u002F\u002Fgithub.com\u002FWaaaalnut\u002Fskillsbench\u002Fblob\u002Fmain\u002Ftasks\u002Fvideo-silence-remover\u002Fenvironment\u002Fskills\u002Fsegment-combiner\u002FSKILL.md",[],[117,151,92,152,153,154,155,156,111,157,158,113,116,159,160,120,161,162],"segment combiner","detection","prepare","merge","video processing","for","outputs","combine","processing","consolidate","results","list",{"skillNo":164,"name":165,"nameZh":6,"description":166,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":9,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":167,"categories":168,"keywords":172,"publishedAt":38},"01M6XEVMPVASGS2KX86QK4FMT7","report-generator","Generate compression reports for video processing. Use when you need to create structured JSON reports with duration statistics, compression ratios, and segment details after video processing.","https:\u002F\u002Fgithub.com\u002FWaaaalnut\u002Fskillsbench\u002Fblob\u002Fmain\u002Ftasks\u002Fvideo-silence-remover\u002Fenvironment\u002Fskills\u002Freport-generator\u002FSKILL.md",[169],{"categoryNo":170,"categoryName":171,"taxonomyType":73,"taxonomyTypeDesc":74},"01JBSEEDCAT000000000000034","行政与办公人员",[173,174,175,117,111,156,116,176,159,177,178,29,120,155,179,92,180,181,109],"generator","report generator","report","with","statistics","structured","json","compression","generate"]