A name earns its place when a reader who has never seen the docs guesses right. This probe measures that: one scenario, three candidate terms swapped in, three models, two runs each. Three arms are the default — when only two candidates are on the table, propose a third synonym and run all three.

Steps

Write the scenario to a file: the domain in two sentences, the shape around the word, and {TERM} where the candidate goes. State only what a stranger needs to place the word, because a scenario that names the meaning under test answers its own question. Close with a fixed answer shape: one sentence plus confidence: high|medium|low, so the runs stay comparable.

Run the probe:

bash .agents/skills/term-check/probe.sh <scenario-file> <term-a> <term-b> <term-c>

Six runs per term, in parallel, about one minute.

Score every run against what the word must convey: right, partly right, or wrong. Keep each model's own confidence line beside its score.
Report the scenario, then the table. Quote the scenario exactly as the models got it, in a fenced block above the table, so the reader judges the question before the answers.

One row per model and run, one column per term. Every cell reads <icon> (<confidence>) -> <guess>: the score as ✅ right, ⚠️ partly right or ❌ wrong, the model's own confidence word, and its guess in a few words, so the reader sees what the model understood. Right answers decide first, confidence second.

Model term-a term-b term-c

Opus, run 1 ✅ (medium) -> moves it to the next day's plan ❌ (low) -> deletes it at the seal ⚠️ (low) -> keeps it somewhere unnamed