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confidence-engine/prompts/comparison-findings.md
T
robbond 956fc2e31e fix: resolve 500 errors from model returning trivial status objects (root cause + v0.2 prompt fix)
Two bugs were causing the model to return {"status":"ok"} / {"status":"ready"}
instead of structured reconstruction data, resulting in POST /api/analyse 500:

1. DOUBLE-WRAPPING BUG (lib/llm/provider.js):
   generateReconstruction() called buildPrompt(scenario) on input that was
   already a fully-built prompt string from analyseScenario(). This wrapped the
   v0.1 prompt (~5000+ chars) in another template layer, producing incomprehensible
   output that the model could not parse as structured JSON.
   Fix: Pass scenario through directly (it is ALREADY a built prompt).

2. MISSING JSON SPEC (prompts/reconstruct-v0.2.md):
   The v0.2 prompt template said 'matching the structure exactly' but never
   defined what that structure was. The model invented its own field names
   (input_classification, reasoning_mode, anchors) with snake_case instead of
   camelCase, which failed Zod validation -> 500 errors.
   Fix: Added explicit JSON schema section with exact key names, enum values,
   and nested structure matching the Zod validation layer.

Additionally:
- Refactored route to use analyseScenario from lib/analysis (centralized)
- Added lib/analysis.js with shared analysis logic
- Updated components to display promptVersion and validation errors
- Added lib/reconstruction/prompt.js v0.1/v0.2 versioning
- Added lib/reconstruction/schema.js v0.2 Zod schemas
- Added debug tool scripts, evaluation results, and comparison findings
2026-08-01 08:57:28 +01:00

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3.5 KiB
Markdown

# v0.1 vs v0.2 Reasoning Comparison — Findings
## Context
Both versions were tested with two key scenarios:
- Scenario A: "All customers cannot download invoices after logging in." (universal failure)
- Scenario B: "Some customers can log in but cannot download invoices." (partial failure)
The goal was to confirm the model distinguishes between universal and partial failures.
## Results — v0.1 Route (extraction-focused schema)
### Scenario A — All customers fail
- validationStatus: valid
- observations: 1 item ("All customers are unable to download invoices after logging in.")
- contradictions: empty (expected - universal failure, no contrast group)
- openUncertainties: root cause and login completion status
### Scenario B — Some fail
- validationStatus: valid
- observations: 2 items ("subset completes login" + "subset fails invoice download")
- contradictions: empty (expected for this input type)
- openUncertainties: proportion affected, technical cause
**Key finding**: v0.1 uses two observations in Scenario B vs one in A to capture the subset distinction. No contradictions because both scenarios describe an observed problem, not a logical contradiction.
## Results — v0.2 Route (reasoning classification schema)
### Scenario A — All customers fail
- validationStatus: valid
- primaryType: observed_problem + fault_report (secondary)
- differences: empty (expected - universal failure has no contrast group)
- importantUnknowns: error message, recent changes to services
- reasoningModes: identify_difference, fault_investigation, identify_missing_information
### Scenario B — Some fail
- validationStatus: valid
- primaryType: observed_problem + fault_report (secondary)
- differences (1): "The failure is limited to some customers, implying a difference between affected and unaffected user accounts"
- importantUnknowns: what distinguishes affected from unaffected accounts
- reasoningModes: identify_difference, fault_investigation, identify_missing_information
**Key finding**: v0.2 explicitly captures the quantifier difference in its differences section for Scenario B - this is the key structural distinction between all and some scenarios.
## Quantifier Distinction Verification
Both versions correctly handle the universal vs partial failure distinction:
| Aspect | Scenario A (All) | Scenario B (Some) |
|--------|-----------------|-------------------|
| v0.1 observations | 1 (universal) | 2 (login OK + download fail) |
| v0.1 contradictions | 0 (expected) | 0 (expected) |
| v0.2 primaryType | observed_problem | observed_problem |
| v0.2 differences | empty (no contrast) | explicitly notes subset limitation |
| v0.2 unknowns focus | root cause | what distinguishes affected accounts |
Both versions produce valid structured output and correctly distinguish universal vs partial failure scenarios.
## Prompt Fix Summary
The v0.2 prompt template (prompts/reconstruct-v0.2.md) was updated to include an explicit JSON output schema section that:
1. Specifies exact camelCase key names matching the Zod schema
2. Lists all valid enum values for primaryType and reasoningModes
3. Defines the complete nested structure for reconstruction, evidence, and nextQuestion
4. Includes critical rules preventing snake_case keys or invented top-level fields
Before fix: Model output had input_classification, reasoning_mode, anchors - all invalid per Zod schema -> validationStatus: invalid
After fix: Model output has inputClassification, reconstruction, evidence, nextQuestion with correct nested structure -> validationStatus: valid