{
  "schemaVersion": "1.0",
  "item": {
    "slug": "text-detection",
    "name": "Text Detection",
    "source": "tencent",
    "type": "skill",
    "category": "AI 智能",
    "sourceUrl": "https://clawhub.ai/raghulpasupathi/text-detection",
    "canonicalUrl": "https://clawhub.ai/raghulpasupathi/text-detection",
    "targetPlatform": "OpenClaw"
  },
  "install": {
    "downloadMode": "redirect",
    "downloadUrl": "/downloads/text-detection",
    "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=text-detection",
    "sourcePlatform": "tencent",
    "targetPlatform": "OpenClaw",
    "installMethod": "Manual import",
    "extraction": "Extract archive",
    "prerequisites": [
      "OpenClaw"
    ],
    "packageFormat": "ZIP package",
    "includedAssets": [
      "SKILL.md"
    ],
    "primaryDoc": "SKILL.md",
    "quickSetup": [
      "Download the package from Yavira.",
      "Extract the archive and review SKILL.md first.",
      "Import or place the package into your OpenClaw setup."
    ],
    "agentAssist": {
      "summary": "Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.",
      "steps": [
        "Download the package from Yavira.",
        "Extract it into a folder your agent can access.",
        "Paste one of the prompts below and point your agent at the extracted folder."
      ],
      "prompts": [
        {
          "label": "New install",
          "body": "I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete."
        },
        {
          "label": "Upgrade existing",
          "body": "I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run."
        }
      ]
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    "sourceHealth": {
      "source": "tencent",
      "status": "healthy",
      "reason": "direct_download_ok",
      "recommendedAction": "download",
      "checkedAt": "2026-04-30T16:55:25.780Z",
      "expiresAt": "2026-05-07T16:55:25.780Z",
      "httpStatus": 200,
      "finalUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=network",
      "contentType": "application/zip",
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        "redirectLocation": null,
        "bodySnippet": null
      },
      "scope": "source",
      "summary": "Source download looks usable.",
      "detail": "Yavira can redirect you to the upstream package for this source.",
      "primaryActionLabel": "Download for OpenClaw",
      "primaryActionHref": "/downloads/text-detection"
    },
    "validation": {
      "installChecklist": [
        "Use the Yavira download entry.",
        "Review SKILL.md after the package is downloaded.",
        "Confirm the extracted package contains the expected setup assets."
      ],
      "postInstallChecks": [
        "Confirm the extracted package includes the expected docs or setup files.",
        "Validate the skill or prompts are available in your target agent workspace.",
        "Capture any manual follow-up steps the agent could not complete."
      ]
    },
    "downloadPageUrl": "https://openagent3.xyz/downloads/text-detection",
    "agentPageUrl": "https://openagent3.xyz/skills/text-detection/agent",
    "manifestUrl": "https://openagent3.xyz/skills/text-detection/agent.json",
    "briefUrl": "https://openagent3.xyz/skills/text-detection/agent.md"
  },
  "agentAssist": {
    "summary": "Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.",
    "steps": [
      "Download the package from Yavira.",
      "Extract it into a folder your agent can access.",
      "Paste one of the prompts below and point your agent at the extracted folder."
    ],
    "prompts": [
      {
        "label": "New install",
        "body": "I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete."
      },
      {
        "label": "Upgrade existing",
        "body": "I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run."
      }
    ]
  },
  "documentation": {
    "source": "clawhub",
    "primaryDoc": "SKILL.md",
    "sections": [
      {
        "title": "Text Detection Skills",
        "body": "Skills for analyzing and detecting AI-generated text content."
      },
      {
        "title": "1. NLP Toolkit",
        "body": "Skill ID: nlp-toolkit\nPurpose: Advanced natural language processing for text analysis\n\nFeatures:\n\nPerplexity calculation\nSentence structure analysis\nEntity extraction\nLanguage detection\nBurstiness measurement\n\nInstallation:\n\nnpm install @clawhub/nlp-toolkit\n\nConfiguration:\n\n{\n  \"skill\": \"nlp-toolkit\",\n  \"settings\": {\n    \"models\": [\"perplexity\", \"entity\", \"language\"],\n    \"cacheResults\": true,\n    \"timeout\": 5000\n  }\n}\n\nUsage:\n\nimport { analyzeText } from '@clawhub/nlp-toolkit';\n\nconst result = await analyzeText(content);\n// {\n//   perplexity: 45.2,\n//   burstiness: 0.65,\n//   entities: ['GPT', 'AI'],\n//   language: 'en',\n//   complexity: 'medium'\n// }\n\nUse Cases:\n\nMeasure text predictability\nDetect AI writing patterns\nAnalyze sentence complexity\nIdentify language and entities\n\nTroubleshooting:\n\nIf slow, enable caching\nFor long text, split into chunks\nLanguage detection requires >100 chars\n\nRelated Skills: pattern-matcher, gpt-analyzer"
      },
      {
        "title": "2. GPT Pattern Analyzer",
        "body": "Skill ID: gpt-analyzer\nPurpose: Detect GPT-specific writing patterns\n\nFeatures:\n\nGPT-3.5/4 signature detection\nCommon phrase identification\nUniform structure detection\nModel fingerprinting\n\nInstallation:\n\nnpm install @clawhub/gpt-analyzer\n\nConfiguration:\n\n{\n  \"skill\": \"gpt-analyzer\",\n  \"settings\": {\n    \"models\": [\"gpt-3.5\", \"gpt-4\"],\n    \"strictMode\": false,\n    \"minConfidence\": 0.7\n  }\n}\n\nUsage:\n\nimport { detectGPT } from '@clawhub/gpt-analyzer';\n\nconst result = await detectGPT(text);\n// {\n//   isGPT: true,\n//   confidence: 0.85,\n//   modelVersion: 'gpt-3.5',\n//   patterns: ['uniform-length', 'formal-tone']\n// }\n\nUse Cases:\n\nIdentify GPT-generated articles\nDetect ChatGPT responses\nAnalyze essays and reports\n\nTroubleshooting:\n\nHigh false positives? Increase minConfidence\nMissing detections? Disable strictMode\nCheck model version matches expected output\n\nRelated Skills: nlp-toolkit, pattern-matcher"
      },
      {
        "title": "3. Pattern Matcher",
        "body": "Skill ID: pattern-matcher\nPurpose: Fast pattern-based detection\n\nFeatures:\n\nRegex pattern library\nSentence structure matching\nRepetitive phrase detection\nFormat consistency analysis\n\nInstallation:\n\nnpm install @clawhub/pattern-matcher\n\nConfiguration:\n\n{\n  \"skill\": \"pattern-matcher\",\n  \"settings\": {\n    \"patterns\": [\n      \"repetitive-starts\",\n      \"uniform-length\",\n      \"formal-markers\"\n    ],\n    \"threshold\": 3\n  }\n}\n\nUsage:\n\nimport { matchPatterns } from '@clawhub/pattern-matcher';\n\nconst result = matchPatterns(text);\n// {\n//   matched: 5,\n//   patterns: ['repetitive-starts', 'uniform-length'],\n//   confidence: 0.65\n// }\n\nUse Cases:\n\nQuick pre-filtering\nSupplement other methods\nReal-time detection\n\nTroubleshooting:\n\nToo many matches? Increase threshold\nAdd custom patterns for specific use cases\nCombine with perplexity for better accuracy\n\nRelated Skills: nlp-toolkit, gpt-analyzer"
      },
      {
        "title": "4. Text Classifier",
        "body": "Skill ID: text-classifier\nPurpose: ML-based text classification\n\nFeatures:\n\nBERT-based classification\nMulti-class support (AI vs human vs mixed)\nFine-tuned on AI text datasets\nFast inference (<200ms)\n\nInstallation:\n\nnpm install @clawhub/text-classifier\n\nUse Cases:\n\nHigh-accuracy classification\nSupplement rule-based methods\nHandle edge cases\n\nRelated Skills: nlp-toolkit"
      },
      {
        "title": "5. Content Hashing",
        "body": "Skill ID: hash-toolkit\nPurpose: Fast content fingerprinting and deduplication\n\nFeatures:\n\nSHA-256, MD5, xxHash\nFuzzy matching\nContent deduplication\nSimilarity scoring\n\nInstallation:\n\nnpm install @clawhub/hash-toolkit\n\nUse Cases:\n\nCache content analysis results\nDetect duplicate content\nFast similarity checks\n\nRelated Skills: All detection skills"
      },
      {
        "title": "6. Sentiment Analyzer",
        "body": "Skill ID: sentiment-analyzer\nPurpose: Analyze text sentiment and tone\n\nFeatures:\n\nPositive/negative/neutral classification\nEmotion detection\nTone analysis (formal, casual, technical)\n\nUse Cases:\n\nDetect AI's typically neutral tone\nIdentify emotional language (more human)\nSupplement detection methods"
      },
      {
        "title": "7. Fact Checker Integration",
        "body": "Skill ID: fact-checker\nPurpose: Verify claims in text\n\nFeatures:\n\nAPI integration with fact-checking services\nClaim extraction\nSource verification\n\nUse Cases:\n\nVerify AI-generated facts\nCross-reference claims\nEnhance trust scoring"
      },
      {
        "title": "Basic Detection Stack",
        "body": "{\n  \"skills\": [\n    \"nlp-toolkit\",\n    \"pattern-matcher\",\n    \"hash-toolkit\"\n  ]\n}\n\nUse for: Quick, lightweight detection"
      },
      {
        "title": "Advanced Detection Stack",
        "body": "{\n  \"skills\": [\n    \"nlp-toolkit\",\n    \"gpt-analyzer\",\n    \"text-classifier\",\n    \"pattern-matcher\",\n    \"hash-toolkit\"\n  ]\n}\n\nUse for: Maximum accuracy, research"
      },
      {
        "title": "Performance-Optimized Stack",
        "body": "{\n  \"skills\": [\n    \"pattern-matcher\",\n    \"hash-toolkit\"\n  ]\n}\n\nUse for: Real-time, high-volume detection"
      },
      {
        "title": "High Accuracy Mode",
        "body": "{\n  \"nlp-toolkit\": {\n    \"models\": [\"perplexity\", \"burstiness\", \"entity\"],\n    \"minTextLength\": 100\n  },\n  \"gpt-analyzer\": {\n    \"strictMode\": true,\n    \"minConfidence\": 0.8\n  },\n  \"text-classifier\": {\n    \"threshold\": 0.9\n  }\n}"
      },
      {
        "title": "Fast Mode",
        "body": "{\n  \"pattern-matcher\": {\n    \"patterns\": [\"basic\"],\n    \"threshold\": 2\n  },\n  \"hash-toolkit\": {\n    \"cacheEnabled\": true,\n    \"algorithm\": \"xxhash\"\n  }\n}"
      },
      {
        "title": "Performance Metrics",
        "body": "SkillSpeedAccuracyMemorynlp-toolkitMedium (500ms)High (85%)50MBgpt-analyzerFast (200ms)High (88%)20MBpattern-matcherVery Fast (<50ms)Medium (65%)5MBtext-classifierMedium (300ms)Very High (92%)100MBhash-toolkitVery Fast (<10ms)N/A1MB"
      },
      {
        "title": "Low Detection Accuracy",
        "body": "Enable all recommended skills\nUse advanced detection stack\nIncrease minTextLength (>100 chars)\nCombine multiple methods and average scores"
      },
      {
        "title": "High False Positives",
        "body": "Increase confidence thresholds\nEnable strictMode\nAdd custom pattern exclusions\nTest on known human text"
      },
      {
        "title": "Slow Performance",
        "body": "Use hash-toolkit for caching\nSwitch to fast mode configuration\nReduce enabled models\nProcess text in background\n\nFor implementation examples and architecture details, see AGENT.SPEC.md and SKILLS_MANAGEMENT.md."
      }
    ],
    "body": "Text Detection Skills\n\nSkills for analyzing and detecting AI-generated text content.\n\nRequired Skills\n1. NLP Toolkit\n\nSkill ID: nlp-toolkit Purpose: Advanced natural language processing for text analysis\n\nFeatures:\n\nPerplexity calculation\nSentence structure analysis\nEntity extraction\nLanguage detection\nBurstiness measurement\n\nInstallation:\n\nnpm install @clawhub/nlp-toolkit\n\n\nConfiguration:\n\n{\n  \"skill\": \"nlp-toolkit\",\n  \"settings\": {\n    \"models\": [\"perplexity\", \"entity\", \"language\"],\n    \"cacheResults\": true,\n    \"timeout\": 5000\n  }\n}\n\n\nUsage:\n\nimport { analyzeText } from '@clawhub/nlp-toolkit';\n\nconst result = await analyzeText(content);\n// {\n//   perplexity: 45.2,\n//   burstiness: 0.65,\n//   entities: ['GPT', 'AI'],\n//   language: 'en',\n//   complexity: 'medium'\n// }\n\n\nUse Cases:\n\nMeasure text predictability\nDetect AI writing patterns\nAnalyze sentence complexity\nIdentify language and entities\n\nTroubleshooting:\n\nIf slow, enable caching\nFor long text, split into chunks\nLanguage detection requires >100 chars\n\nRelated Skills: pattern-matcher, gpt-analyzer\n\n2. GPT Pattern Analyzer\n\nSkill ID: gpt-analyzer Purpose: Detect GPT-specific writing patterns\n\nFeatures:\n\nGPT-3.5/4 signature detection\nCommon phrase identification\nUniform structure detection\nModel fingerprinting\n\nInstallation:\n\nnpm install @clawhub/gpt-analyzer\n\n\nConfiguration:\n\n{\n  \"skill\": \"gpt-analyzer\",\n  \"settings\": {\n    \"models\": [\"gpt-3.5\", \"gpt-4\"],\n    \"strictMode\": false,\n    \"minConfidence\": 0.7\n  }\n}\n\n\nUsage:\n\nimport { detectGPT } from '@clawhub/gpt-analyzer';\n\nconst result = await detectGPT(text);\n// {\n//   isGPT: true,\n//   confidence: 0.85,\n//   modelVersion: 'gpt-3.5',\n//   patterns: ['uniform-length', 'formal-tone']\n// }\n\n\nUse Cases:\n\nIdentify GPT-generated articles\nDetect ChatGPT responses\nAnalyze essays and reports\n\nTroubleshooting:\n\nHigh false positives? Increase minConfidence\nMissing detections? Disable strictMode\nCheck model version matches expected output\n\nRelated Skills: nlp-toolkit, pattern-matcher\n\n3. Pattern Matcher\n\nSkill ID: pattern-matcher Purpose: Fast pattern-based detection\n\nFeatures:\n\nRegex pattern library\nSentence structure matching\nRepetitive phrase detection\nFormat consistency analysis\n\nInstallation:\n\nnpm install @clawhub/pattern-matcher\n\n\nConfiguration:\n\n{\n  \"skill\": \"pattern-matcher\",\n  \"settings\": {\n    \"patterns\": [\n      \"repetitive-starts\",\n      \"uniform-length\",\n      \"formal-markers\"\n    ],\n    \"threshold\": 3\n  }\n}\n\n\nUsage:\n\nimport { matchPatterns } from '@clawhub/pattern-matcher';\n\nconst result = matchPatterns(text);\n// {\n//   matched: 5,\n//   patterns: ['repetitive-starts', 'uniform-length'],\n//   confidence: 0.65\n// }\n\n\nUse Cases:\n\nQuick pre-filtering\nSupplement other methods\nReal-time detection\n\nTroubleshooting:\n\nToo many matches? Increase threshold\nAdd custom patterns for specific use cases\nCombine with perplexity for better accuracy\n\nRelated Skills: nlp-toolkit, gpt-analyzer\n\nRecommended Skills\n4. Text Classifier\n\nSkill ID: text-classifier Purpose: ML-based text classification\n\nFeatures:\n\nBERT-based classification\nMulti-class support (AI vs human vs mixed)\nFine-tuned on AI text datasets\nFast inference (<200ms)\n\nInstallation:\n\nnpm install @clawhub/text-classifier\n\n\nUse Cases:\n\nHigh-accuracy classification\nSupplement rule-based methods\nHandle edge cases\n\nRelated Skills: nlp-toolkit\n\n5. Content Hashing\n\nSkill ID: hash-toolkit Purpose: Fast content fingerprinting and deduplication\n\nFeatures:\n\nSHA-256, MD5, xxHash\nFuzzy matching\nContent deduplication\nSimilarity scoring\n\nInstallation:\n\nnpm install @clawhub/hash-toolkit\n\n\nUse Cases:\n\nCache content analysis results\nDetect duplicate content\nFast similarity checks\n\nRelated Skills: All detection skills\n\nOptional Skills\n6. Sentiment Analyzer\n\nSkill ID: sentiment-analyzer Purpose: Analyze text sentiment and tone\n\nFeatures:\n\nPositive/negative/neutral classification\nEmotion detection\nTone analysis (formal, casual, technical)\n\nUse Cases:\n\nDetect AI's typically neutral tone\nIdentify emotional language (more human)\nSupplement detection methods\n7. Fact Checker Integration\n\nSkill ID: fact-checker Purpose: Verify claims in text\n\nFeatures:\n\nAPI integration with fact-checking services\nClaim extraction\nSource verification\n\nUse Cases:\n\nVerify AI-generated facts\nCross-reference claims\nEnhance trust scoring\nSkill Combinations\nBasic Detection Stack\n{\n  \"skills\": [\n    \"nlp-toolkit\",\n    \"pattern-matcher\",\n    \"hash-toolkit\"\n  ]\n}\n\n\nUse for: Quick, lightweight detection\n\nAdvanced Detection Stack\n{\n  \"skills\": [\n    \"nlp-toolkit\",\n    \"gpt-analyzer\",\n    \"text-classifier\",\n    \"pattern-matcher\",\n    \"hash-toolkit\"\n  ]\n}\n\n\nUse for: Maximum accuracy, research\n\nPerformance-Optimized Stack\n{\n  \"skills\": [\n    \"pattern-matcher\",\n    \"hash-toolkit\"\n  ]\n}\n\n\nUse for: Real-time, high-volume detection\n\nSkill Configuration Examples\nHigh Accuracy Mode\n{\n  \"nlp-toolkit\": {\n    \"models\": [\"perplexity\", \"burstiness\", \"entity\"],\n    \"minTextLength\": 100\n  },\n  \"gpt-analyzer\": {\n    \"strictMode\": true,\n    \"minConfidence\": 0.8\n  },\n  \"text-classifier\": {\n    \"threshold\": 0.9\n  }\n}\n\nFast Mode\n{\n  \"pattern-matcher\": {\n    \"patterns\": [\"basic\"],\n    \"threshold\": 2\n  },\n  \"hash-toolkit\": {\n    \"cacheEnabled\": true,\n    \"algorithm\": \"xxhash\"\n  }\n}\n\nPerformance Metrics\nSkill\tSpeed\tAccuracy\tMemory\nnlp-toolkit\tMedium (500ms)\tHigh (85%)\t50MB\ngpt-analyzer\tFast (200ms)\tHigh (88%)\t20MB\npattern-matcher\tVery Fast (<50ms)\tMedium (65%)\t5MB\ntext-classifier\tMedium (300ms)\tVery High (92%)\t100MB\nhash-toolkit\tVery Fast (<10ms)\tN/A\t1MB\nTroubleshooting\nLow Detection Accuracy\nEnable all recommended skills\nUse advanced detection stack\nIncrease minTextLength (>100 chars)\nCombine multiple methods and average scores\nHigh False Positives\nIncrease confidence thresholds\nEnable strictMode\nAdd custom pattern exclusions\nTest on known human text\nSlow Performance\nUse hash-toolkit for caching\nSwitch to fast mode configuration\nReduce enabled models\nProcess text in background\n\nFor implementation examples and architecture details, see AGENT.SPEC.md and SKILLS_MANAGEMENT.md."
  },
  "trust": {
    "sourceLabel": "tencent",
    "provenanceUrl": "https://clawhub.ai/raghulpasupathi/text-detection",
    "publisherUrl": "https://clawhub.ai/raghulpasupathi/text-detection",
    "owner": "raghulpasupathi",
    "version": "1.0.0",
    "license": null,
    "verificationStatus": "Indexed source record"
  },
  "links": {
    "detailUrl": "https://openagent3.xyz/skills/text-detection",
    "downloadUrl": "https://openagent3.xyz/downloads/text-detection",
    "agentUrl": "https://openagent3.xyz/skills/text-detection/agent",
    "manifestUrl": "https://openagent3.xyz/skills/text-detection/agent.json",
    "briefUrl": "https://openagent3.xyz/skills/text-detection/agent.md"
  }
}