Implement the three-dimensional assessment (phase, progress, conversation
health) that sits between narrative and behaviour selection.
Key changes:
- lib/assessment/investigation-state-assessor.js: assessor module with
countObservations, assessPhase, assessProgress, assessConversationHealth,
assessInvestigationState — deterministic classifiers using known rules
- tests/investigation-state-assessor.test.js: 51 tests covering phase
classification (orienting→concluding), progress thresholds, health
conditions, confidence aggregation, edge cases, and observation counting
- lib/graph/orchestrator.js: integration calls passing correctly-shaped input
to assessInvestigationState() at three call sites (~552, ~904, ~1013)
Design decisions encoded in this iteration:
- countObservations counts nodes with known/resolved status + high-confidence
non-unknown non-state nodes (not just explicit observation-kind nodes)
- Phase uses seven values including cannot_determine for insufficient data
- Progress uses resolution ratio thresholds: accelerating (>0.6), steady
(0.2-0.6), stalled (<0.2 with ≥1 resolved)
- Overall confidence = minimum across all three dimensions (conservative)
Also adds investigation-state-assessment-contract.md and updates
design-evolution-log, investigation-state-assessment.md (status header),
and investigation-turn-cycle.md (implementation status table).
Close Experiment 15 (Facilitator Behaviour Specification).
Introduce Experiment 16 — Investigation State Assessment.
- Create docs/investigation-state-assessment.md with 7 assessment dimensions:
Current Investigation Phase, Investigation Progress, Evidence Quality,
Understanding Trajectory, Uncertainty Trend, Conversation Health,
and Behaviour Readiness. Each dimension includes purpose, observable
signals, possible values, and how behaviours may consume it.
- Document 6 assessment principles (Assess Not Decide, All Signals
Traceable to Narrative, Descriptive Not Prescriptive, Convergence Over
Single Signal, Stateful Across Turns, Uncertainty About Assessment Is
Itself Assessable).
- Include exploratory decision matrix linking investigation states to
likely behaviours with reasons.
- Prepend Behaviour Selection section to docs/facilitator-behaviour.md
recording that behaviours are selected from Investigation State
Assessment and do not inspect graph nodes directly.
- Update docs/design-evolution-log.md: close Experiment 15, add
Experiment 16 closure, record emerging architecture with the new layer
between Narrative and Behaviour Selection.
No implementation. Documentation only. No changes to reasoning engine,
graph generation, prompts, orchestrator, APIs, Ollama integration, or UI.
robbond