Motivation

A general-purpose agent can always produce a number. The hard part is producing a range that is honest enough to use and structured enough to improve.

The problem

Two common approaches fail in opposite ways:

• A quick point estimate is cheap but hides the uncertainty that controls the decision.
• Open-ended research collects more facts but often lacks a threshold, source hierarchy, or stopping rule.

Both can create confident output without decision value. A third failure—simulation laundering—adds mathematical machinery to weak assumptions and makes the result look more trustworthy than it is.

The mental model

Measurement is valuable when it changes a decision. The workflow therefore begins with the decision threshold, decomposes the uncertain quantity, and buys information only where it can change the action.

A range is not an admission of failure. It is the honest shape of the available knowledge.

Key design decisions

• Decision before research. A threshold determines which uncertainty matters. (Consequence: vague prompts sometimes require clarification before browsing.)
• Ranges before simulation. Calibrated inputs carry the real epistemic work. (Consequence: the skill refuses decorative Monte Carlo output.)
• Source provenance in the memo. Facts, assumptions, and inference remain distinguishable. (Consequence: the memo is longer than a bare answer.)
• A structured appendix, not a structured substitute. JSON supports reuse while the prose preserves reasoning. (Consequence: every output has two representations to keep aligned.)
• Missing inputs stay missing. Blocked estimates use null numeric fields and an explicit status. (Consequence: the workflow sometimes declines to estimate.)

Alternatives considered

• A single reusable prompt. Too easy for an agent to skip thresholds, source grading, or verification.
• A calculator-only tool. Reliable arithmetic, but no judgment about target mode, evidence quality, or decision relevance.
• A simulation-first workflow. Precise output cannot rescue uncalibrated inputs.
• A full HTMA suite as a hard dependency. More power, but worse portability. Companion skills remain optional.

Non-goals

HTMA Measure is not:

• a guarantee that uncertain forecasts become accurate;
• a replacement for authoritative current data;
• a license to infer private financial facts;
• a full statistical software package; or
• a substitute for reviewing sources and assumptions.