the-mindscape-of-bro-tsong/selector

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
• Model-level hard exclusion 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

Round 03.2 selector rule:

• Explicit refusal of a specific model, such as 不要思想考古 or 只做 QPI, is a model-level hard exclusion for that model.
• A hard exclusion rejects only the named model; it does not globally no-call the request.
• Generic bare QPI gate words such as 如何 and 判断 should not be used alone. Use compound problem-definition phrases instead.

Round 03.2a selector rule:

• Depth-limiting phrases such as 不要展开 and 不要深入分析 remain global no-call signals by default.
• If a depth-limiting phrase is paired with explicit QPI-limited intent such as 只做 QPI, 只做问题定性, or 只判断主导稀缺, the selector should continue scoring, allow QPI, and still reject IA.

Round 04.1 selector rule:

• Translation / direct transformation instructions should no-call even when the payload contains complexity words such as 模型.
• Task instruction and payload content should be separated for no-call routing when a direct transformation phrase appears before a colon.
• IA refusal variants such as 不要进入思想考古 and 不做思想考古 are model-level hard exclusions for IA.
• Depth-limiting phrases paired with 主导稀缺 or 缺信息 / 缺路径 / 缺共识 intent should allow QPI and reject IA.

Round 05.1 selector rule:

• Governance / responsibility / consensus wording is not enough by itself to select QPI.
• Narrow QPI positive signals are allowed when the input includes responsibility ambiguity, direction collapse, commitment waiting, decision authority gaps, minimum-path uncertainty, or stable-output blockage.
• Capacity wording remains no-call when it only expresses an execution constraint.
• Ambiguous low-context inputs such as 还是那个老问题 should no-call instead of selecting QPI by the bare word 问题.
• Default QPI-before-IA remains unchanged.
• Natural-language prior-QPI claims still keep lightweight QPI review; structured prior_qpi_result selector support is not implemented in Round 05.1.

Current files:

• selector_rules.json
• selector_examples.json
• selector_calibration_inputs.json
• round04_blind_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.

Round 04 blind routing evaluation is scripts/run_round04_blind_routing.py.

Round 04.1 post-patch routing verification is scripts/run_round04_post_patch_verification.py.

Round 05.1 selector patch audit is scripts/run_round05_1_selector_patch_audit.py.

round04_blind_inputs.json is a frozen blind input pool for first-run routing evaluation. It intentionally contains no expected selector behavior and should not be merged into calibration inputs before owner / GPT / CCRA review.

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.