experiment: test question relevance against decision target

docs/design-evolution-log.md

@@ -1101,6 +1101,26 @@ Further evidence is still required if the classifier is to be considered viable.
 
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+### Experiment 20 — Conclusion
+
+The hypothesis was not confirmed by this evaluation.
+
+**What happened:**
+
+- The passive classifier collapsed to a single category (`incidental`) across the long-investigation scenario.
+- Three independent factors caused the collapse: no downstream dependencies, missed decision-text patterns (regex required "whether to" but questions used "Whether [clause]"), and zero graph edges on active unknowns.
+- The keyword-only approach produced technically correct but practically useless classifications.
+
+**What this means:**
+
+Question importance cannot be judged in isolation from the decision being investigated. A question like "Do we have competitive differentiation?" is only important when compared against a clear decision target. Without that target, keyword matching and local graph structure are insufficient signals.
+
+**Decision:**
+
+The Experiment 20 classifier has not been accepted into the active engine. Its rules remain unchanged (do not expand them). The next step is Experiment 21: testing whether providing an explicit decision target allows a simple deterministic classifier to produce useful distinctions.
+
+---
+
 ## Phase Transition
 
 Record that the project has moved from:
@@ -1139,6 +1159,45 @@ The objective is to make the investigation feel like a natural facilitated conve
 
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+### Experiment 21 — Question Relevance Against Decision Target
+
+#### Hypothesis
+
+Does giving the classifier an explicit decision target allow it to distinguish questions that could change the decision from questions that are merely useful or incidental?
+
+This is one question. Nothing else matters until this is answered.
+
+#### Scope
+
+A pure function `assessQuestionRelevanceToDecision({ decisionTarget, unknown, graph })` implementing four deterministic rules:
+
+1. **could_change_decision** — The question directly mirrors the decision's core action (e.g., "whether to enter", "should we launch", "whether there is [demand/market/need]") AND the decision target contains a matching action keyword. Answering could reasonably reverse the proposed action.
+2. **supports_decision** — Necessary precondition (e.g., compliance, cost feasibility) OR supporting context (e.g., differentiation, competitive position). The answer would improve confidence or evidence but is less likely to reverse the decision alone.
+3. **unlikely_to_change_decision** — Background detail or comparative reference that does not affect the decision conditions.
+4. **cannot_determine** — Decision target or unknown is missing, empty, or too unclear to compare honestly.
+
+The classifier is passive — validated only against mock scenario fixtures. No changes to: graph construction, question importance classifier, unknown selection, question selection, prompts, Ollama integration, APIs, UI, state assessment, behaviour selection, conversation output, or engine behaviour in any way.
+
+#### Decision Target
+
+For the long-investigation scenario, use an explicit target from the fixture:
+
+> Should we enter the European market with our SaaS analytics platform?
+
+Do not attempt to discover the decision target automatically. For this experiment, the decision target is supplied by the test fixture.
+
+#### Evaluation
+
+Run the classifier passively across the same long-investigation turns used in Experiment 20 (turns 0–3). Record per-turn classification. Compare with Experiment 20 results. Expect at least two distinct categories — not a collapse to one.
+
+#### Questions
+
+- Does providing an explicit decision target enable more useful distinctions than keyword-only matching?
+- Do the four categories map intuitively to how a human evaluator would judge relevance?
+- Or does the deterministic rule set still miss cases that appear obviously important?
+
+---
+
 ## Current Open Questions
 
 The following are active explorations rather than decisions.