{
  "title": "Empirical distribution viewer",
  "human_url": "https://happytails.ai/en/calculators/empirical-distribution-viewer/",
  "agent_url": "https://happytails.ai/agents/en/calculators/empirical-distribution-viewer/",
  "language": "en",
  "markdown_url": "https://happytails.ai/en/calculators/empirical-distribution-viewer.md",
  "content": "Empirical distribution viewer\nPlot your observations as a cumulative distribution and read percentiles without fitting a model.\nHow can we improve this tool?\nReport a problem or share an idea.\nPlease leave out private information. Your message and the tool name go to our team via PostHog.\nHow to use Empirical distribution viewer\nPaste your observations using decimal points.\nChoose a percentile and a threshold for cumulative probability.\nInspect the step chart and download the complete values.\nUseful next steps\nProbability calculator\nBayes theorem visualizer\nRead the model\nPlot your observations as a cumulative distribution and read percentiles without fitting a model.\nCheck the definition\nUp to 10,000 finite values, each between −1 trillion and 1 trillion, and one million input characters. Use decimal points, separated by spaces, commas or semicolons. Duplicates retain their weight. Percentiles use the inverse empirical CDF (type 1), with zero returning the minimum. The plot combines steps within the same horizontal pixel; table, CSV and JSON keep every distinct value. This describes the sample and does not estimate population probabilities.\nKeep the calculation\nDownload SVG for the chart, JSON for unrounded values, CSV for the table and the assumptions note. Your input stays on your device.",
  "content_format": "text/plain",
  "visibility": "public",
  "links": [
    {
      "name": "Probability calculator",
      "url": "https://happytails.ai/en/calculators/probability-calculator/"
    },
    {
      "name": "Bayes theorem visualizer",
      "url": "https://happytails.ai/en/calculators/bayes-theorem-visualizer/"
    }
  ],
  "tool": {
    "id": "empirical-distribution-viewer",
    "category": "calculators",
    "built": true,
    "requirements": "Up to 10,000 finite values, each between −1 trillion and 1 trillion, and one million input characters. Use decimal points, separated by spaces, commas or semicolons. Duplicates retain their weight. Percentiles use the inverse empirical CDF (type 1), with zero returning the minimum. The plot combines steps within the same horizontal pixel; table, CSV and JSON keep every distinct value. This describes the sample and does not estimate population probabilities.",
    "implementation": {
      "fields": [
        {
          "key": "percentile",
          "label": "Percentile (%)",
          "value": 50,
          "type": "number",
          "min": 0,
          "max": 100,
          "step": "any"
        },
        {
          "key": "threshold",
          "label": "Threshold value",
          "value": 0,
          "type": "number",
          "min": -1000000000000,
          "max": 1000000000000,
          "step": "any"
        }
      ],
      "live": true,
      "background": true,
      "presentation": "metrics",
      "inputMaxLength": 1000000,
      "inputErrorCode": "STAT_SIZE",
      "note": "Paste up to 10,000 finite numbers separated by spaces, commas or semicolons. Use decimal points. Read the right-continuous cumulative fraction and the inverse empirical percentile (type 1). No distribution is fitted.",
      "experience": {
        "automatic": true,
        "single": false,
        "inputMaxLength": 1000000,
        "inputMode": "text",
        "label": "Your text",
        "placeholder": "Type or paste your input…",
        "help": "Change the input or settings to update your result. Results update as you type. Up to 1,000,000 characters.",
        "action": null
      },
      "mode": "automatic",
      "interactive": false
    },
    "execution": "Browser interface",
    "api": null,
    "browser_agent": {
      "supported": true,
      "name": "run_current_tool",
      "discovery": "WebMCP on the human page in a supporting browser",
      "verification": "See audit/API-AUDIT.md; availability is not verification"
    }
  },
  "markdown": "# Empirical distribution viewer\n\n- Human page: https://happytails.ai/en/calculators/empirical-distribution-viewer/\n- Markdown: https://happytails.ai/en/calculators/empirical-distribution-viewer.md\n- Structured JSON: https://happytails.ai/agents/en/calculators/empirical-distribution-viewer/index.json\n- Visibility: public\n\n## Tool capabilities\n\n| Property | Value |\n| --- | --- |\n| Tool ID | `empirical-distribution-viewer` |\n| Category | calculators |\n| Implementation | Registered implementation. Registration alone is not a production-quality guarantee. |\n| Browser execution | Automatic updates after valid input or file selection. |\n| Browser processing | Browser; see tool notes for network behavior. |\n| HTTP API | Not callable through HTTP. |\n| Browser-agent interface | run_current_tool |\n\n### Implementation notes\n\nPaste up to 10,000 finite numbers separated by spaces, commas or semicolons. Use decimal points. Read the right-continuous cumulative fraction and the inverse empirical percentile (type 1). No distribution is fitted.\n\n### Inputs and settings\n\nText input: Your text.\n\nExample or placeholder shown in the interface (not a validated fixture):\n\n```text\nType or paste your input…\n```\n\nChange the input or settings to update your result. Results update as you type. Up to 1,000,000 characters.\n\n| Setting | Meaning | Control type | Default | Constraints |\n| --- | --- | --- | --- | --- |\n| `percentile` | Percentile (%) | number | 50 | min=0 max=100 step=any |\n| `threshold` | Threshold value | number | 0 | min=-1000000000000 max=1000000000000 step=any |\n\n### Browser-agent workflow\n\n1. Open the human page in a browser that supports WebMCP.\n2. Discover the interface exposed by that page; use its actual schema.\n3. Select files on the page first when the tool requires files.\n4. Call `run_current_tool` with valid input and settings.\n5. Inspect the returned result or error and the displayed output. Retrieve files from the displayed download links.\n\nCalls do not automatically copy or download results. Browser permissions still apply. Interface availability alone is not proof of successful execution.\n\n### Planning specification\n\nUp to 10,000 finite values, each between −1 trillion and 1 trillion, and one million input characters. Use decimal points, separated by spaces, commas or semicolons. Duplicates retain their weight. Percentiles use the inverse empirical CDF (type 1), with zero returning the minimum. The plot combines steps within the same horizontal pixel; table, CSV and JSON keep every distinct value. This describes the sample and does not estimate population probabilities.\n\nThis describes intended requirements. Use the implementation notes, interface schema and observed output to determine current support.\n\n### Complete machine-readable capability record\n\n```json\n{\n  \"id\": \"empirical-distribution-viewer\",\n  \"category\": \"calculators\",\n  \"built\": true,\n  \"requirements\": \"Up to 10,000 finite values, each between −1 trillion and 1 trillion, and one million input characters. Use decimal points, separated by spaces, commas or semicolons. Duplicates retain their weight. Percentiles use the inverse empirical CDF (type 1), with zero returning the minimum. The plot combines steps within the same horizontal pixel; table, CSV and JSON keep every distinct value. This describes the sample and does not estimate population probabilities.\",\n  \"implementation\": {\n    \"fields\": [\n      {\n        \"key\": \"percentile\",\n        \"label\": \"Percentile (%)\",\n        \"value\": 50,\n        \"type\": \"number\",\n        \"min\": 0,\n        \"max\": 100,\n        \"step\": \"any\"\n      },\n      {\n        \"key\": \"threshold\",\n        \"label\": \"Threshold value\",\n        \"value\": 0,\n        \"type\": \"number\",\n        \"min\": -1000000000000,\n        \"max\": 1000000000000,\n        \"step\": \"any\"\n      }\n    ],\n    \"live\": true,\n    \"background\": true,\n    \"presentation\": \"metrics\",\n    \"inputMaxLength\": 1000000,\n    \"inputErrorCode\": \"STAT_SIZE\",\n    \"note\": \"Paste up to 10,000 finite numbers separated by spaces, commas or semicolons. Use decimal points. Read the right-continuous cumulative fraction and the inverse empirical percentile (type 1). No distribution is fitted.\",\n    \"experience\": {\n      \"automatic\": true,\n      \"single\": false,\n      \"inputMaxLength\": 1000000,\n      \"inputMode\": \"text\",\n      \"label\": \"Your text\",\n      \"placeholder\": \"Type or paste your input…\",\n      \"help\": \"Change the input or settings to update your result. Results update as you type. Up to 1,000,000 characters.\",\n      \"action\": null\n    },\n    \"mode\": \"automatic\",\n    \"interactive\": false\n  },\n  \"execution\": \"Browser interface\",\n  \"api\": null,\n  \"browser_agent\": {\n    \"supported\": true,\n    \"name\": \"run_current_tool\",\n    \"discovery\": \"WebMCP on the human page in a supporting browser\",\n    \"verification\": \"See audit/API-AUDIT.md; availability is not verification\"\n  }\n}\n```\n\n## Page guide\n\nPlot your observations as a cumulative distribution and read percentiles without fitting a model.\n\nHow can we improve this tool?\n\nReport a problem or share an idea.\n\nPlease leave out private information. Your message and the tool name go to our team via PostHog.\n\n### How to use Empirical distribution viewer\n\n1. Paste your observations using decimal points.\n2. Choose a percentile and a threshold for cumulative probability.\n3. Inspect the step chart and download the complete values.\n\n## Useful next steps\n\n- [Probability calculator](https://happytails.ai/en/calculators/probability-calculator/) ([Markdown](https://happytails.ai/en/calculators/probability-calculator.md))\n\n- [Bayes theorem visualizer](https://happytails.ai/en/calculators/bayes-theorem-visualizer/) ([Markdown](https://happytails.ai/en/calculators/bayes-theorem-visualizer.md))\n\n## Read the model\n\nPlot your observations as a cumulative distribution and read percentiles without fitting a model.\n\n### Check the definition\n\nUp to 10,000 finite values, each between −1 trillion and 1 trillion, and one million input characters. Use decimal points, separated by spaces, commas or semicolons. Duplicates retain their weight. Percentiles use the inverse empirical CDF (type 1), with zero returning the minimum. The plot combines steps within the same horizontal pixel; table, CSV and JSON keep every distinct value. This describes the sample and does not estimate population probabilities.\n\n### Keep the calculation\n\nDownload SVG for the chart, JSON for unrounded values, CSV for the table and the assumptions note. Your input stays on your device.\n"
}