Academic Unslop Skill

Description

Detect AI-writing risk patterns in English and Chinese thesis text — English text uses the conservative D1–D17 framework, Chinese text uses the Chinese-text AI-risk module plus shared structure-level checks, and mixed documents are routed by language segment — score paragraph-level and document-level AI risk, and rewrite high-risk sections by reducing shared external-detector-sensitive features such as repeated templates, uniform rhythm, mechanical reporting sequences, and over-smooth academic reasoning. The scoring system is intentionally conservative and calibrated for structural AI-risk signals commonly detected by external AI detection systems in formal master's thesis writing.

This skill should not treat a low internal score as proof that the text is safe. When a known detector result is available, such as Turnitin AI = 48%, use it as a calibration signal and adjust the internal scoring more strictly.

Core Operating Architecture (READ FIRST — overrides any conflicting rule below)

Multiple failure modes have been observed in real multi-round use, including score regression, structural over-editing, word-count loss, readability damage, detector-comparison error, and unsupported researcher-trace insertion. The rules in this section exist to prevent them and override any conflicting rule anywhere else in this file.

Principle 0 — The goal is a TARGET, not merely "lower than last time"

The operational objective is to reduce traceable AI-writing-risk patterns in user-provided thesis text and to prepare candidate revisions for comparable external re-test. The target threshold (default 30%, or a stricter value the user specifies) is used only as a closed-loop stopping condition when comparable detector evidence exists; the skill must never guarantee, imply, or optimise for a detector outcome independently of academic integrity, meaning preservation, and evidence-based revision. Chapter scores are the primary closed-loop units; the whole-document score is a target only when a comparable whole-document external test is available. "Lower than the previous version" is NOT success. A version that is the lowest so far but still above the active target is NOT finished — it is work in progress.

Authorized-Use Boundary: this skill may be used only on thesis text the user owns, authored, co-authored, or is explicitly authorized to edit. It supports clarity, academic integrity, and detector-informed risk diagnosis; it must NOT be used to misrepresent authorship, hide prohibited AI use, fabricate research contribution, or bypass an institution's disclosure or assessment rules.

T19/T29 Master Boundary Rule: T19 is relocation or light integration of researcher-side material that already exists elsewhere in the thesis; T19 never creates new interpretive content. T29 is evidence-based reconstruction; T29 may add a new interpretive sentence only when a completed Source Trace block proves it is grounded in existing thesis materials, codes, quotations, methods, findings, or cited literature. For qualitative passages, any new interpretive sentence must use T29, never T19. If a source trace cannot be established, write "Author confirmation needed" instead of adding the sentence.