---
id: T01
parent: S03
milestone: M013
provides: []
requires: []
affects: []
key_files: ["backend/pipeline/quality/variant_generator.py", "backend/pipeline/quality/optimizer.py"]
key_decisions: ["Variant validation uses both length diff and line-level symmetric difference to catch trivial mutations", "OptimizationLoop bypasses VoiceDial — the loop owns the full prompt text directly"]
patterns_established: []
drill_down_paths: []
observability_surfaces: []
duration: ""
verification_result: "Both modules import cleanly: `python -c "from pipeline.quality.variant_generator import PromptVariantGenerator"` and `python -c "from pipeline.quality.optimizer import OptimizationLoop, OptimizationResult"` both exit 0."
completed_at: 2026-04-01T09:07:58.463Z
blocker_discovered: false
---

# T01: Created PromptVariantGenerator (LLM-powered prompt mutation) and OptimizationLoop (iterative generate→score→select engine) with full error tolerance and progress reporting

> Created PromptVariantGenerator (LLM-powered prompt mutation) and OptimizationLoop (iterative generate→score→select engine) with full error tolerance and progress reporting

## What Happened
---
id: T01
parent: S03
milestone: M013
key_files:
  - backend/pipeline/quality/variant_generator.py
  - backend/pipeline/quality/optimizer.py
key_decisions:
  - Variant validation uses both length diff and line-level symmetric difference to catch trivial mutations
  - OptimizationLoop bypasses VoiceDial — the loop owns the full prompt text directly
duration: ""
verification_result: passed
completed_at: 2026-04-01T09:07:58.464Z
blocker_discovered: false
---

# T01: Created PromptVariantGenerator (LLM-powered prompt mutation) and OptimizationLoop (iterative generate→score→select engine) with full error tolerance and progress reporting

**Created PromptVariantGenerator (LLM-powered prompt mutation) and OptimizationLoop (iterative generate→score→select engine) with full error tolerance and progress reporting**

## What Happened

Built two modules in backend/pipeline/quality/. variant_generator.py provides PromptVariantGenerator with a meta-prompt instructing the LLM to act as a prompt engineer — generates N variants targeting weakest dimensions, validates each (min diff + format markers), skips invalid ones. optimizer.py provides OptimizationLoop that orchestrates load→baseline score→iterate(generate→score→select)→report cycles, with OptimizationResult capturing full history for downstream leaderboard/charting.

## Verification

Both modules import cleanly: `python -c "from pipeline.quality.variant_generator import PromptVariantGenerator"` and `python -c "from pipeline.quality.optimizer import OptimizationLoop, OptimizationResult"` both exit 0.

## Verification Evidence

| # | Command | Exit Code | Verdict | Duration |
|---|---------|-----------|---------|----------|
| 1 | `python -c "from pipeline.quality.variant_generator import PromptVariantGenerator; print('generator ok')"` | 0 | ✅ pass | 500ms |
| 2 | `python -c "from pipeline.quality.optimizer import OptimizationLoop, OptimizationResult; print('optimizer ok')"` | 0 | ✅ pass | 500ms |


## Deviations

OptimizationLoop._score_variant does its own synthesis call rather than delegating to ScoreRunner.synthesize_and_score() to avoid VoiceDial double-application since the loop owns the full prompt text directly.

## Known Issues

None.

## Files Created/Modified

- `backend/pipeline/quality/variant_generator.py`
- `backend/pipeline/quality/optimizer.py`


## Deviations
OptimizationLoop._score_variant does its own synthesis call rather than delegating to ScoreRunner.synthesize_and_score() to avoid VoiceDial double-application since the loop owns the full prompt text directly.

## Known Issues
None.
