• RISK SCORE
  • RELIABILITY
  • ADVICE
  • HUMAN

How to assess peeking risk with your AI client

Connect once, then let your agent handle the math. It checks if your current data is enough to make a call without inflating your error rates.

Ask AI about this page

Short answer

Can I stop my A/B test early without ruining the math?

Peeking at results before reaching your target sample size increases the chance of a false positive. Your agent calculates the specific risk of stopping now and tells you how much more data you need. You'll get a clear picture of your statistical reliability.

The outcomes of a risk check.

Where your results land.

The AI processes your experiment data to provide these specific insights.

RISK SCORE

Quantified peeking error

The AI uses assess_peeking_risk to find the probability that your current observed effect is a false positive. You get a single number representing your statistical risk.

RELIABILITY

Confidence level check

Your agent compares your current sample size against the required threshold. It tells you if your current data is stable or just noise.

ADVICE

Next steps for testing

The AI calculates how much more data you actually need to reach significance. It provides the specific sample size required to hit your target power.

HUMAN

Final decision making

The AI provides the math, but you decide if the risk is worth the business move. You weigh the statistical error against the cost of waiting.

The workflow

What your AI does when the data arrives.

Your agent handles the heavy lifting of the statistical calculations.

  1. Analyze current state

    Your agent looks at your current conversion rates, baseline, and current sample size to understand the experiment's progress.

    assess_peeking_risk

  2. Calculate error probability

    The AI runs the math to see how much the Type I error rate has drifted due to early observation.

    assess_peeking_risk

  3. Project required volume

    It determines the remaining sample size needed to restore your intended statistical power.

    assess_peeking_risk

  4. Summarize findings

    Your agent translates the raw statistical outputs into a plain English report on whether to keep running or stop.

    assess_peeking_risk

Try it

Copy these to start.

Paste these prompts into your chat to begin the assessment.

Starting points

Replace the bracketed details with your actual experiment numbers like conversion rates or current sample counts.

AB Test Sample Size Calculator Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_r2w7FicRhYLb2yLUrh65lss0cEO4Bcdo5mApGeZ1/mcp

Claude Desktop

Follow the steps below to connect in seconds.

  1. 1In Claude Desktop, open Settings → Connectors.
  2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
  3. 3Click Add and start a new chat — AB Test Sample Size Calculator capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "ab-test-sample-size-calculator-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_r2w7FicRhYLb2yLUrh65lss0cEO4Bcdo5mApGeZ1/mcp"
    }
  }
}
Copy into chat04

  • Assess the peeking risk for my current test. The baseline conversion is 5%, the variant is 5.5%, and I have 1,200 users in each group.

  • I want to stop my experiment early. Check if my current sample size of 5,000 users is enough to avoid a false positive.

  • Calculate how many more users I need to reach a 95% confidence level for this test given my current results.

  • Run a peeking risk check on my experiment data from this spreadsheet. The current lift is 10% with 800 samples per variant.

  • Claude
  • ChatGPT
  • Cursor
  • VS Code
  • Windsurf
  • Claude Code
  • JetBrains
  • Cline

Start here

Connect AB Test Sample Size Calculator once, then ask.

Connect the MCP to your preferred client. Once connected, your agent can immediately run these statistical checks on your data.

Connect AB Test Sample Size Calculator to your AI

FAQ

How this task behaves

  • 01

    Can the AI change my experiment settings in my testing tool?

    No. The AI only reads your data and performs calculations. It cannot modify your live experiments or change settings in external platforms.

  • 02

    Does the AI automatically stop my test if the risk is too high?

    No. The AI provides the risk assessment and the math, but you must make the final decision to stop or continue the test.

  • 03

    What data do I need to provide for an accurate check?

    You need to provide the baseline conversion rate, the observed lift, the current sample size per variant, and your desired significance level.

  • 04

    Can the AI fix my statistical errors?

    No. It can only identify that an error has occurred and tell you how much more data is needed to correct it.

  • 05

    How does it handle different confidence levels?

    The AI uses the parameters you provide to calculate the specific risk for your chosen confidence threshold.

  • More questions about AB Test Sample Size Calculator? The Connector page answers them. See everything the AB Test Sample Size Calculator Connector can do

Connect AB Test Sample Size Calculator to Claude, Cursor, ChatGPT & more