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    "slug": "figure-legend-gen",
    "name": "Figure Legend Gen",
    "source": "tencent",
    "type": "skill",
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    "summary": "Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.",
    "steps": [
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      "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",
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  "documentation": {
    "source": "clawhub",
    "primaryDoc": "SKILL.md",
    "sections": [
      {
        "title": "Figure Legend Generator",
        "body": "Generate publication-quality figure legends for scientific research charts and images."
      },
      {
        "title": "Supported Chart Types",
        "body": "Chart TypeDescriptionBar ChartCompare values across categoriesLine GraphShow trends over time or continuous dataScatter PlotDisplay relationships between variablesBox PlotShow distribution and outliersHeatmapDisplay matrix data intensityMicroscopyFluorescence/confocal imagesFlow CytometryFACS plots and histogramsWestern BlotProtein expression bands"
      },
      {
        "title": "Usage",
        "body": "python scripts/main.py --input <image_path> --type <chart_type> [--output <output_path>]"
      },
      {
        "title": "Parameters",
        "body": "ParameterRequiredDescription--inputYesPath to chart image--typeYesChart type (bar/line/scatter/box/heatmap/microscopy/flow/western)--outputNoOutput path for legend text (default: stdout)--formatNoOutput format (text/markdown/latex), default: markdown--languageNoLanguage (en/zh), default: en"
      },
      {
        "title": "Examples",
        "body": "# Generate legend for bar chart\npython scripts/main.py --input figure1.png --type bar\n\n# Save to file\npython scripts/main.py --input plot.jpg --type line --output legend.md\n\n# Chinese output\npython scripts/main.py --image.png --type scatter --language zh"
      },
      {
        "title": "Legend Structure",
        "body": "Generated legends follow academic standards:\n\nFigure Number - Sequential numbering\nBrief Title - Concise description\nMain Description - What the figure shows\nData Details - Key statistics/measurements\nMethodology - Brief experimental context\nStatistics - P-values, significance markers\nScale Bars - For microscopy images"
      },
      {
        "title": "Technical Notes",
        "body": "Difficulty: Low\nDependencies: PIL, pytesseract (optional OCR)\nProcessing: Vision analysis for chart type detection\nOutput: Structured markdown by default"
      },
      {
        "title": "References",
        "body": "references/legend_templates.md - Templates by chart type\nreferences/academic_style_guide.md - Formatting guidelines"
      },
      {
        "title": "Risk Assessment",
        "body": "Risk IndicatorAssessmentLevelCode ExecutionPython scripts with toolsHighNetwork AccessExternal API callsHighFile System AccessRead/write dataMediumInstruction TamperingStandard prompt guidelinesLowData ExposureData handled securelyMedium"
      },
      {
        "title": "Security Checklist",
        "body": "No hardcoded credentials or API keys\n No unauthorized file system access (../)\n Output does not expose sensitive information\n Prompt injection protections in place\n API requests use HTTPS only\n Input validated against allowed patterns\n API timeout and retry mechanisms implemented\n Output directory restricted to workspace\n Script execution in sandboxed environment\n Error messages sanitized (no internal paths exposed)\n Dependencies audited\n No exposure of internal service architecture"
      },
      {
        "title": "Prerequisites",
        "body": "# Python dependencies\npip install -r requirements.txt"
      },
      {
        "title": "Success Metrics",
        "body": "Successfully executes main functionality\n Output meets quality standards\n Handles edge cases gracefully\n Performance is acceptable"
      },
      {
        "title": "Test Cases",
        "body": "Basic Functionality: Standard input → Expected output\nEdge Case: Invalid input → Graceful error handling\nPerformance: Large dataset → Acceptable processing time"
      },
      {
        "title": "Lifecycle Status",
        "body": "Current Stage: Draft\nNext Review Date: 2026-03-06\nKnown Issues: None\nPlanned Improvements:\n\nPerformance optimization\nAdditional feature support"
      }
    ],
    "body": "Figure Legend Generator\n\nGenerate publication-quality figure legends for scientific research charts and images.\n\nSupported Chart Types\nChart Type\tDescription\nBar Chart\tCompare values across categories\nLine Graph\tShow trends over time or continuous data\nScatter Plot\tDisplay relationships between variables\nBox Plot\tShow distribution and outliers\nHeatmap\tDisplay matrix data intensity\nMicroscopy\tFluorescence/confocal images\nFlow Cytometry\tFACS plots and histograms\nWestern Blot\tProtein expression bands\nUsage\npython scripts/main.py --input <image_path> --type <chart_type> [--output <output_path>]\n\nParameters\nParameter\tRequired\tDescription\n--input\tYes\tPath to chart image\n--type\tYes\tChart type (bar/line/scatter/box/heatmap/microscopy/flow/western)\n--output\tNo\tOutput path for legend text (default: stdout)\n--format\tNo\tOutput format (text/markdown/latex), default: markdown\n--language\tNo\tLanguage (en/zh), default: en\nExamples\n# Generate legend for bar chart\npython scripts/main.py --input figure1.png --type bar\n\n# Save to file\npython scripts/main.py --input plot.jpg --type line --output legend.md\n\n# Chinese output\npython scripts/main.py --image.png --type scatter --language zh\n\nLegend Structure\n\nGenerated legends follow academic standards:\n\nFigure Number - Sequential numbering\nBrief Title - Concise description\nMain Description - What the figure shows\nData Details - Key statistics/measurements\nMethodology - Brief experimental context\nStatistics - P-values, significance markers\nScale Bars - For microscopy images\nTechnical Notes\nDifficulty: Low\nDependencies: PIL, pytesseract (optional OCR)\nProcessing: Vision analysis for chart type detection\nOutput: Structured markdown by default\nReferences\nreferences/legend_templates.md - Templates by chart type\nreferences/academic_style_guide.md - Formatting guidelines\nRisk Assessment\nRisk Indicator\tAssessment\tLevel\nCode Execution\tPython scripts with tools\tHigh\nNetwork Access\tExternal API calls\tHigh\nFile System Access\tRead/write data\tMedium\nInstruction Tampering\tStandard prompt guidelines\tLow\nData Exposure\tData handled securely\tMedium\nSecurity Checklist\n No hardcoded credentials or API keys\n No unauthorized file system access (../)\n Output does not expose sensitive information\n Prompt injection protections in place\n API requests use HTTPS only\n Input validated against allowed patterns\n API timeout and retry mechanisms implemented\n Output directory restricted to workspace\n Script execution in sandboxed environment\n Error messages sanitized (no internal paths exposed)\n Dependencies audited\n No exposure of internal service architecture\nPrerequisites\n# Python dependencies\npip install -r requirements.txt\n\nEvaluation Criteria\nSuccess Metrics\n Successfully executes main functionality\n Output meets quality standards\n Handles edge cases gracefully\n Performance is acceptable\nTest Cases\nBasic Functionality: Standard input → Expected output\nEdge Case: Invalid input → Graceful error handling\nPerformance: Large dataset → Acceptable processing time\nLifecycle Status\nCurrent Stage: Draft\nNext Review Date: 2026-03-06\nKnown Issues: None\nPlanned Improvements:\nPerformance optimization\nAdditional feature support"
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    "sourceLabel": "tencent",
    "provenanceUrl": "https://clawhub.ai/AIPOCH-AI/figure-legend-gen",
    "publisherUrl": "https://clawhub.ai/AIPOCH-AI/figure-legend-gen",
    "owner": "AIPOCH-AI",
    "version": "1.0.0",
    "license": null,
    "verificationStatus": "Indexed source record"
  },
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