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discoveredlabs.com

discoveredlabs.com

live Unverified (seed import) Productivity & Business 2 tools imperative implementation

AEO/GEO agency that helps B2B companies get recommended in AI search results when customers ask AI assistants for suggestions.

First seen 2026-10-12 · Last seen 2026-10-12 · Source: webmcp.com

Answer 0 · Act 1 · Transact 1 · Score: Not yet scored

Tool inspector

calculate_eval_sample_size

act imperative

Calculate the statistically valid number of prompts and API calls for an LLM brand-mention evaluation. Call when planning an eval; pass confidence (default 95), margin_of_error_pct (default 2), resamples_per_prompt (default 3), var_between and var_within. Returns unique_prompts and total_api_calls.

Input schema

PropertyTypeRequiredDescription
confidence number no Statistical confidence level as a percentage (default 95)
margin_of_error_pct number no Acceptable margin of error as a percentage (default 2)
resamples_per_prompt number no Number of times to resample each prompt to reduce within-question noise (default 3)
var_between number no Between-question variance — how much brand mention rates differ across different questions (default 0.02)
var_within number no Within-question variance — how much the model wobbles when answering the same question (default 0.05)
Raw JSON schema
{
  "type": "object",
  "properties": {
    "confidence": {
      "type": "number",
      "description": "Statistical confidence level as a percentage (default 95)",
      "minimum": 80,
      "maximum": 99,
      "default": 95
    },
    "margin_of_error_pct": {
      "type": "number",
      "description": "Acceptable margin of error as a percentage (default 2)",
      "minimum": 0.5,
      "maximum": 5,
      "default": 2
    },
    "resamples_per_prompt": {
      "type": "number",
      "description": "Number of times to resample each prompt to reduce within-question noise (default 3)",
      "minimum": 1,
      "maximum": 20,
      "default": 3
    },
    "var_between": {
      "type": "number",
      "description": "Between-question variance — how much brand mention rates differ across different questions (default 0.02)",
      "minimum": 0,
      "maximum": 0.1,
      "default": 0.02
    },
    "var_within": {
      "type": "number",
      "description": "Within-question variance — how much the model wobbles when answering the same question (default 0.05)",
      "minimum": 0,
      "maximum": 0.2,
      "default": 0.05
    }
  },
  "required": []
}

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