Tools

Evaluation and reliability calculators

Calculators for AI agent eval statistics: confidence intervals, paired significance, repeated-run reliability, judge calibration, agreement and bias, prompt robustness, and RAG.

• Agent Loop Cap Calculator

  Paste your agent's step counts. Get the iteration cap your coverage target implies, the share of work the cap would cut, and a dollar ceiling for your unattended window.

• Acceptable Error Rate Calculator: The Reliability Bar Automation Needs

  Invert your own manual cost, automation cost, and consequence cost into the minimum reliability that makes automating pay, and see if a measured rate clears it.

• Eval Run Register: Preregistration and Run Cards for LLM Evals

  Keep one row per eval run in this browser: freeze the plan before results exist, log what happened, and export a run card or a preregistration record for a PR.

• Expected Cost of Failure Calculator for AI Agents

  Price a failure rate in money: what gets caught, what escapes, and what correction and rework savings are worth, split by failure class.

• Reproducibility Checklist and Manifest Validator

  Check whether your write-up records what someone else would need to rerun your eval: a checklist against the published card schema, and a validator for a pasted or uploaded manifest.

• Agent Action Risk Matrix: Which Actions Need an Approval Gate

  Place every action your agent can take on two axes: whether anything undoes it, and its blast radius, the field's name for propagation radius. Each row returns a written control level, never a score.

• Paired vs Independent: Choosing an Eval Comparison Design

  Six questions give you the design, the test that fits it, the rules that fired, and what the branch you did not pick costs in cases and model runs.

• pass^k, pass@k and reliability@k Estimator: Chance That All k Runs Pass

  Estimate per-task pass^k and suite-level reliability@k from repeated eval runs, with Wilson and Student-t confidence intervals and the unbiased pass@k capability counterpart.

• Irreversible Action Inventory: What Your Agent Cannot Take Back

  List every action your agent can take, mark what reverses it, and name the point of no return. A written verdict per row, never a score or a budget.

• Golden Set Size Planner: How Many Examples an Eval Set Needs

  Size a golden set from a baseline pass rate, a margin, and the drop worth catching: items per slice, a total, and a verdict on the set you already have.

• Wilson and Clopper-Pearson Pass-Rate Confidence Interval Calculator

  Turn an eval pass rate (k of n) into a defensible confidence interval: Wilson score, Clopper-Pearson exact, and Wald normal bounds side by side.

• Repeated-Run Variance Planner: How Many Trials per Eval Case

  Split your eval's spread into run-to-run and case-to-case variance, then read the trials per case, the case count that implies, and the protocol to freeze.

• Eval Sample Size and Power Calculator

  Find how many eval runs you need to detect a pass-rate drop at a target power, across two-arm, fixed-baseline, and paired McNemar designs.

• Judge Validation Report Builder: Report, Version Card, Drift Plan

  Fill one form and keep three documents: a validation report showing your LLM judge was checked against people, a version card pinning the prompt and settings, and a drift plan with a date on it.

• Eval Budget Calculator: What an LLM Evaluation Run Will Cost

  Price an eval plan before you run it: cases by variants by trials by judge calls, plus the human review hours it needs, from your own rates.

• McNemar Test Calculator for Paired Eval Runs

  Run McNemar's paired significance test on two eval runs scored on the same items, with exact and chi-square p-values and a CI on the pass-rate difference.

• Harness Migration Score Continuity Checker

  Separate what the harness moved from what your system moved. Feed the overlap bridge and your eval results to see the harness offset, the system-attributable change and a restated baseline.

• Multi-Step Agent Reliability Calculator (Independent Steps)

  Compute the end-to-end success rate of a multi-step agent chain from its per-step reliability, and the per-step budget your target reliability demands.

• Cohen's Kappa Calculator (Two Raters): Inter-Rater Reliability

  Cohen's kappa from the four counts of a 2x2 table: chance-corrected agreement between two raters, with a confidence interval and an interpretation band. Built for an LLM judge against human labels.

• LLM Judge Bias Correction Calculator

  Correct an LLM judge's raw pass rate for its measured sensitivity and specificity (the Rogan-Gladen correction), then report a calibration-aware confidence interval on the true rate.

• LLM Judge Position Bias Calculator (Swap-Consistency Test)

  Score a pairwise LLM judge on order-swapped pairs: swap-consistency and position-preference rates with Wilson intervals and an exact test for position bias.

• RAG Chunk Size Calculator: Index Size and Context Budget

  Size a RAG index from its chunking plan: chunk size, overlap, and top-k give the vector count, storage inflation, and context-budget share. Which size retrieves best stays a measured question.

• LLM Token Counter: Context Budget and Cost per Attempt

  Count tokens for a named model, see what the request reserves in the context window once output is set aside, and price one attempt at your own rates. Exact where we bundle the encoding.

• LLM Judge Calibration Calculator: Brier Score and ECE

  Score an LLM judge's stated confidence against observed correctness: Brier score, expected and maximum calibration error, a reliability diagram, and the error rate behind its confident verdicts.

• LLM Eval A/B Comparator: Paired Difference with Bootstrap CIs

  Run an LLM eval A/B test on paired graded scores: mean score difference with a bootstrap confidence interval, paired effect size, and win/tie/loss evidence.

• Pairwise Win Rate Calculator with Elo and Bradley-Terry Ratings

  Turn pairwise LLM judge comparisons between models or prompts into win rates with Wilson intervals, Bradley-Terry strengths on the Elo scale, and a plain read on whether the advantage is real.

• Human Review Threshold Optimizer for Confidence-Gated Automation

  Derive the human review threshold from your own records: paste stated confidence and observed correctness, price one review against one missed failure, and read the cut that costs least.

• Fleiss' Kappa, Krippendorff's Alpha and ICC Calculator

  Agreement among three or more raters or LLM judges: Fleiss' kappa, Krippendorff's alpha, Gwet's AC1 and intraclass correlation, with percent agreement, bootstrap intervals, and per-rater diagnostics.

• Judge Agreement Tracker: Log Kappa Over Time

  Keep a dated log of one judge's agreement with human labels: the value, the prompt version and set behind it, the published band it falls in, the change since the last run, and the next check date.

• Retry, Verification, and Fallback Reliability Optimizer for LLM Agents

  How many times should you retry a failed agent step? Compare retry, majority vote, verifier gate, fallback, and escalation on delivered correctness and expected cost per task, from your own rates.

• Your judge disagrees with your humans. Which bias explains it?

  Paste judge and human labels. See which bias mode explains the gap, ranked by how much each one accounts for, then follow the link to the calculator that tests it.

• AI SLO Error Budget Calculator: Split a Failure Budget Across Classes

  Turn a completion-rate target and a task volume into a failure budget split by class, with a Wilson interval on each class observed rate against its allowance.

• Benchmark Rank Uncertainty Calculator: Score Intervals and Rank Ranges

  Put error bars on an LLM benchmark leaderboard. Paste scores with item counts, correct-of-total, or standard errors and see which adjacent ranks are a statistical tie.

• Prompt Robustness Analyzer: Perturbation Stability for LLM Evals

  Is a prompt's pass-rate drop real or noise? Paste pass/fail results for a baseline prompt and its semantically equivalent variants and read each change with a paired interval and an exact McNemar p.

• RAG Retrieval Quality Calculator: Precision@K, Recall@K, nDCG, MRR, MAP

  Score a retrieval run per query and across the suite: Precision@K, Recall@K, Hit@K, nDCG, mean reciprocal rank (MRR), and mean average precision (MAP), with a K sweep and intervals.

• Multi-Step Agent Reliability with Shared Failures (Cascade Simulator)

  Price a multi-step agent chain when its steps share a cause: end-to-end reliability under common-cause failure beside the independent figure, plus the retry ceiling that shared failures impose.

• Eval Dataset Schema Validator: Golden-Set Checks and Export Profiles

  Check an eval golden set against a neutral schema in your browser: findings by row and line, duplicate ids, field completeness, plus a template and exports for four eval tools.

• Exact Duplicate Row Checker for Eval and Golden Datasets

  Find byte-identical rows in an eval or golden dataset without uploading it. Duplicate groups with row and line numbers, an identity key you choose, and the sample size left after a dedupe.

• Near-Duplicate Row Detector: Find Eval Rows That Differ Only in Formatting

  Find rows in an eval set that are the same test written twice. Normalize the columns you pick, group rows whose normalized text matches, and read the exact transform, the raw variants, and a CSV.

• Cross-Split Overlap Checker: Find Eval Items in Both Train and Test

  Compare two eval splits in your browser and see which items sit on both sides, with a separate overlap rate against the row count of each split, exact and normalized matching, and the lines to open.

• N-Gram Overlap Checker: Find Contamination Between Two Eval Files

  Check a test set against a training file for shared word sequences. Pick n, read the per-row dirty-token share, see the matching text in both files, and export a CSV. Both files stay in your browser.

• Slice and Class Balance Analyzer: See What an Eval Set Contains

  Read what an eval set holds before you quote a pass rate. Count rows per slice, per class, and per control flag, put an interval on every share, and see the smallest slice named.

• Cost per Successful Task Calculator: What One Acceptable Result Costs

  Turn a per-attempt price and a pass rate into the cost of one acceptable result, with retries, failed attempts, review and the fallback path all priced into the total.

• Evaluation Card Generator: Markdown and JSON on a Published Schema

  Write one evaluation down so a second person can read the number correctly, or run it again. Fill the form, export a Markdown card and a JSON card that validates against a schema published here.

• Golden Set Version Tracker: Dataset Diff and Changelog

  Diff two versions of your golden eval set in the browser, keep a dated changelog of what changed and why, and freeze the baseline metric values the next run is judged against.

• Release Gate Designer: Go/No-Go Rules and Decision Log

  Write the rule that turns your eval figures into PROMOTE, HOLD or ROLLBACK, get the verdict plus the rule that produced it, and keep a dated decision log and memo in your browser.

• Change Impact Worksheet: What to Rerun Before You Ship

  Describe one change to a shipped AI system and get the rerun list it invalidates: which suites, slices and graders to run again, why each is on the list, and a change record for the ticket.

• AI Model Deprecation Dates, Replacements and Breaking Changes

  Retirement dates, vendor replacements and what breaks in your eval when you swap.

• Independent Two-Proportion Test Calculator for Eval Arms

  Compare two pass rates measured on different case sets: a pooled two-proportion z test, Fisher exact when an arm is small, and an interval on the difference.

• Context-of-Use Profiler: Turn a System Description into Evaluation Consequences

  Describe what your AI system does, who it affects and how it fails, and get the failure families, case classes, slices and evidence expectations those answers demand.

• Agent Trace Analyzer: Step Counts, Repeated Calls, Handoff Edges

  Upload an agent run trace and get step counts, repeated-call detection with index ranges, handoff edges, and per-class run tallies. Deterministic checks on the file you already have.

• LLM Latency Budget Calculator: TTFT and Token Time Across a Chain

  Compose per-step time-to-first-token and token-stream latency into a chain deadline. See which step spends the budget, what kind of time it spends, and the timeout each layer should hold.

• Evaluation Blueprint Builder: Write the Argument Before You Run the Eval

  State each claim your evaluation will make, name the evidence that would support or refute it, and write the inference step connecting the two, all before any results exist.

• MCP Tool Surface Auditor

  Audit an MCP tool surface or diff two manifests for breaking changes. Paste your tools/list output. Nothing from the manifest you paste is sent anywhere.

• Risk-to-Test Mapper: Which Failures Need Which Cases

  Name the failures you care about, then see the test-case shapes, slices, evaluators and metrics each one needs. Every mapping says what it cannot establish. The mapping is a LatentEval synthesis.

• Evaluation Coverage Matrix: Which Cells Have No Cases

  Put what you test on one axis and what you test it across on the other. The grid shows which cells have cases, which are empty, which are too small to carry an interval, and what each gap costs you.

• Evaluator and Metric Navigator: Which Grader, Which Number

  Answer four questions about oracle type, grader, system count, and failure mode. Get the admissible evaluator, inadmissible ones and why, the metric family, and a route to the tool that runs it.

• What Does This Evaluation Prove?

  Select the evidence your evaluation produced, see which claims it supports, which it cannot, and the inference error behind each gap. Each unsupported claim names the instrument that would close it.

• Acceptance Criteria Builder: Set the Bar Before the Run

  State each pass/fail criterion, the risk axes it covers, the reasoning behind the threshold and who set it. Get the sample size each one needs and export the rules for the release gate designer.

• Golden Set Blueprint Builder: Seed a Test Set From a Task Family

  Choose a task family, load its case taxonomy and starter rows, then edit, add and export. Every row carries an oracle type and a provenance tag, and the export validates against the eval-set schema.

• Claim-Evidence Matrix: What Backs Each Deployment Claim

  One row per deployment claim, eleven evidence dimensions from relevance and representativeness to independence and applicability, with named rate-down reasons and residual deficits.