134 lines
4.2 KiB
Markdown
134 lines
4.2 KiB
Markdown
# QPI
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model_id: qpi
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file: models/qpi.md
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runtime_scope: minimal_v0
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governance_level: draft_callable
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status: callable
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model_level: L2_callable_model
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default_role: routing_model
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allowed_roles: routing_model, calibration_model
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reader_translation_required: true
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## One-Sentence Definition
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QPI classifies how a cognitive subject frames an expectation-reality gap as `question`, `problem`, `issue`, `mixed`, or `no_call`, then identifies missing context, dominant scarcity, dynamic stage, and misframing risk.
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## Runtime Role
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QPI is a front-routing and misframing-diagnostic model.
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It should run before deep processing when problem framing is unclear. It should not replace deep processing, synthesis, or final answer generation.
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## Core Question
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Who, in what scenario, frames which expectation-reality gap as what kind of problem, and what context is missing before the framing can be trusted?
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## Core Mechanism
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QPI checks:
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- problem owner;
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- subject position;
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- scenario context;
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- responsibility scope;
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- problem source;
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- time scale;
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- expectation-reality gap;
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- three scarcity types.
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Scarcity mapping:
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- `question`: data or fact scarcity;
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- `problem`: path, method, or resource scarcity;
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- `issue`: consensus, certainty, order, or dynamic-balance scarcity;
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- `mixed`: multiple scarcity types in the same subject/scenario frame;
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- `no_call`: input does not need QPI.
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QPI must distinguish same-frame mixed scarcity from cross-viewpoint divergence.
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## Call When
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- The user asks what the real problem is.
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- The input mixes facts, path constraints, interests, and system structure.
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- The problem owner or responsibility boundary is unclear.
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- The user is rushing to solve before defining the issue.
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- There is risk of violent reduction, malicious inflation, or means-end mismatch.
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- A later model needs routing support.
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## Do Not Call When
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- The user only asks for a clear fact lookup.
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- The user gives a direct execution task.
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- The user asks for copyediting or format conversion.
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- The problem has already been framed and only needs the next execution step.
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- The user explicitly asks not to analyze, unless they narrowly request QPI-only classification.
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## Input Types
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- ambiguous problem statement;
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- business or product issue description;
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- organizational conflict narrative;
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- unclear requirement or failure report;
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- owner reflection that needs problem-definition help.
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## Output Contract
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QPI output must include:
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- `classification_scope`: `subject_contextual | multi_perspective | insufficient_context | no_call`;
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- `classification`: `question | problem | issue | mixed | no_call`;
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- `classification_confidence`: `high | medium | low`;
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- `is_provisional`;
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- `problem_owner`;
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- `subject_position`;
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- `scenario_context`;
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- `responsibility_scope`;
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- `problem_source`;
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- `time_scale`;
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- `expectation_reality_gap`;
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- `context_sufficiency`;
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- `missing_context`;
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- `scarcity_profile`;
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- `dominant_scarcity`;
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- `classification_reason`;
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- `classification_by_viewpoint`;
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- `dynamic_stage`;
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- `possible_trajectory`;
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- `success_criteria_stability`;
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- `hard_feedback_availability`;
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- `governance_load`;
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- `evidence_gap`;
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- `misclassification_risk`;
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- `recommended_clarifying_questions`;
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- `recommended_next_step`;
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- `next_model_candidates`.
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## Depth Control
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Stop at QPI when:
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- the input is a fact lookup;
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- classification evidence is too thin;
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- the user only needs a narrow problem-type judgment;
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- negative triggers suppress analysis.
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Recommend `intellectual_archaeology` only when the issue is high-value, recurring, structurally complex, or likely to benefit from depth processing.
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## Common Misuses
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- Treating QPI as a full answer.
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- Turning QPI into the main governance battlefield.
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- Classifying by keywords without owner/scenario context.
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- Calling every complex-looking input an `issue`.
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- Collapsing cross-viewpoint divergence into same-frame `mixed`.
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- Using QPI to delay a direct fact lookup or simple execution task.
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## Source Seed Notes
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Seeded from the old QPI model/card and Wantsong cognitive-system source material, rewritten for this runtime. Old regression suites, selector calibration, and review artifacts are not migrated.
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## Current Limits
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This model is callable for manual runtime use, but it is not a reviewed core model. It needs real-run evidence before any upgrade.
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