Introduction
HTMA Measure is a portable agent skill for estimating uncertain quantities when a decision depends on the answer. It works for project costs, budgets, vendor quotes, rates, risks, ROI, market size, revenue, and similar questions where a precise-looking guess would be misleading.
The skill converts a vague question into a measurement memo with:
- a precise decision and threshold;
- an explicit quantity, unit, and time horizon;
- confirmed facts separated from assumptions and inference;
- a low / central / high decomposition;
- a calibrated confidence interval;
- the uncertainty most worth reducing next;
- a recommendation tied to the decision; and
- a machine-readable
HTMA_RESULTJSON appendix.
The key difference
Section titled “The key difference”HTMA Measure asks which range the evidence supports, how that range affects the decision, and what evidence would be worth collecting next.
The workflow addresses these common failures:
- False precision: a single number disguises uncertainty.
- Research without a stopping rule: the agent gathers easy facts that cannot change the decision.
- Simulation laundering: Monte Carlo output makes weak assumptions look rigorous.
What HTMA means here
Section titled “What HTMA means here”The workflow draws on decision-focused measurement and calibrated estimation ideas popularized by Douglas W. Hubbard’s How to Measure Anything. This repository is an independent implementation and is not affiliated with or endorsed by the author or publisher.