Abhijit Balaji 6c94c4d9ca feat(prompt-optimization): implement multi-objective evaluation metrics ...

Established a Pareto-ready evaluation foundation for the Genetic-Pareto (GEPA)
optimizer, supporting simultaneous optimization of accuracy and density.

Key improvements:
- Core Architecture: Defined standardized `MetricResult` and `OptimizationDirection`
  types in `packages/core/src/evals/types.ts` to support multi-objective fitness.
- Centralized Config: Implemented `packages/core/src/evals/config.ts` with tunable
  weights and detailed documentation for scoring gradients.
- Tool Alignment Metric: Created `metrics/toolAlignment.ts` to measure functional
  accuracy, argument precision, and explicit shell avoidance.
- Token Frugality Metric: Created `metrics/tokenFrugality.ts` to measure and
  penalize conversational noise ("chatter") using a configurable threshold.
- Verification Suite: Added comprehensive unit tests for all metrics, achieving
  100% coverage of scoring logic and gradient steps.
- Project Integration: Relocated `schema.ts` to the core package for build safety,
  updated the data validator, and extended project-wide lint/format scripts.

2026-03-04 10:08:14 -08:00

..

manifest.json

feat(prompt-optimization): implement Data Layer MVP and Tool Alignment dataset

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tool_alignment.jsonl

feat(prompt-optimization): implement Data Layer MVP and Tool Alignment dataset

2026-03-04 10:08:13 -08:00