# Selector

This folder contains rule-based selector configuration and examples.

The v0.2 selector should not call an LLM.

It should use simple matching rules:

- Trigger keywords
- Input types
- Negative triggers
- Pipeline position
- Selection priority
- Negative trigger first
- No-call threshold
- QPI-before-IA gate
- QPI positive-signal gate
- Direct-execution no-call signals
- Calibration smoke checks

Current files:

- `selector_rules.json`
- `selector_examples.json`
- `selector_calibration_inputs.json`
- `qpi_case_digests.json`

The selector does not call an LLM.

The executable demo is `scripts/run_selector_demo.py`.

Selector regression is `scripts/run_selector_regression.py`.

Selector calibration smoke check is `scripts/run_selector_calibration_smoke.py`.

`qpi_case_digests.json` stores owner-reviewed QPI case digests that can feed selector calibration or later regression selection. It is not a model status upgrade and should not include unreviewed draft cases.

Digest field notes:

- `misclassification_risk` is the canonical digest field matching QPI's structured output contract.
- `qpi_complexity_pattern` records judgment complexity: `not_mixed`, `intra_frame_mixed`, or `inter_viewpoint_divergence`.
- `qpi_complexity_pattern=intra_frame_mixed` does not imply `classification=mixed`; `classification` is the final routing class, while `qpi_complexity_pattern` records the structure of the judgment.
- Multi-perspective / inter-viewpoint cases require `classification_by_viewpoint` or `viewpoint_summary`.