Scholar Reasoning Distiller

Problem Being Solved

When a reader has a passage from a scholar and wants to continue writing, reviewing, or debating using that scholar’s concepts, methods, citations, and boundaries, generic LLMs often imitate surface tone while missing the underlying reasoning structure. Scholar Reasoning Distiller addresses this by turning textual signals such as ontology, conceptual distinctions, analytic operations, evaluation thresholds, intertextual habits, rhetorical rhythm, refusal boundaries, and diachronic change into reusable constraints.

How It Works

The skill has two stages. In the distillation stage, it extracts information from user-provided articles, notes, interviews, or other texts using the eight-layer reasoning extraction framework. Features seen once are recorded as tentative; features seen twice or more are marked stable, and later texts can accumulate the fingerprint. In the deployment stage, the nine-module skill architecture acts as a pre-check, including Scope, Activation, Ontological, Procedural, Evaluative, Intertextual, Rhetorical, Refusal, and Provenance. Users can select one of four tasks: peer review, doctoral supervision, lecturing, or panel discussion. Each response includes quantitative scoring and qualitative commentary; for example, peer review checks standard, proportion, defensibility, actionability, and consistency, while lecturing checks accuracy, structure, layering, learnability, and robustness to follow-up questions.

Boundaries and Notes

This skill is suitable for personal study, writing support, speculative simulation, and research warnings. It is not suitable for falsifying peer review, deceiving academic institutions, or replacing a scholar’s compensated labor. It depends on sufficient source texts; short excerpts can only produce weak tentative fingerprints. The output is a simulation of reasoning style, not the full thought of the scholar, and public publications should be used under fair quotation principles.