Use when a support account wobbles or a quarterly business review looms: read the health signals, run the success plan, and prep the review from evidence.
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Write an experiment readout with assignment checks, metric definitions, sample sizes, uncertainty, practical effect, and limits.
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Run score Not tested
See how to installReview the instructions the agent will receive before you install.
Use this for a controlled experiment or a clearly labelled quasi-experiment. Do not call a before-and-after comparison an A/B test.
Capture the hypothesis written before the test, unit of assignment, eligibility, variants, allocation, exposure event, start and end times, stopping rule, primary metric, guardrails, analysis window, exclusions, and planned segments. Name any field that was chosen after results were visible.
Check sample-ratio mismatch, duplicate assignment, cross-variant exposure, missing exposure, unequal data delay, pre-test balance on available baseline fields, instrumentation changes, and novelty or calendar effects. State how each fault limits the result.
For every primary and guardrail metric show control and variant sample sizes, raw values, absolute effect, relative effect where useful, uncertainty interval or other approved uncertainty measure, and missing-data rate. Put the primary metric first. Keep exploratory metrics and segments in a separate section.
Discuss practical size, not only statistical significance. A result can be uncertain, too small to matter, or harmful on a guardrail. State whether the data supports ship, do not ship, continue, or no decision under the owner's pre-agreed rule; the named owner makes the decision.
List deviations from plan, unmeasured outcomes, affected population, follow-up window, and what the result does not prove. Give the next test only when it answers a stated open question.
Never change the primary metric or stopping rule without disclosure, omit an unfavourable guardrail, invent significance, or generalise past the tested population. Protect personal data. Route tests with legal, medical, credit, employment, or safety impact to the responsible expert before action.
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Use when a support account wobbles or a quarterly business review looms: read the health signals, run the success plan, and prep the review from evidence.
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Reconcile accounts by comparing GL balances to subledgers, bank statements, or third-party data. Use when performing bank reconciliations, GL-to-subledger recs, intercompany reconciliations, or identifying and categorizing reconciling items.
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Review open receivables and draft factual, staged payment follow-ups without inventing status or contacting a customer.
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Write ad variants that each test one idea, within platform limits and supported claims.
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Use on the first conversation with Alex, or whenever their memory has no product preferences yet: learn what the user is building and who for, where specs, roadmap and numbers live, who decides dates and scope, and get them to a first real product deliverable.
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Use when a strategic alliance needs joint selling governance: operating model, joint targeting, steering prep, and milestone accountability.
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