What problem does it solve? When a text analyzes AI while AI itself helped produce that text, the resulting reflexive loop is often ignored, overstated, or mischaracterized. This Skill provides a rigorous analytical procedure to reconstruct what AI actually did during the writing process and determine whether that participation creates meaningful consequences for claims about authorship, cognition, agency, and responsibility. ## Core Features & Use Cases - Role Reconstruction: Identifies the AI's actual functions (polishing, organizing, testing, generating, connecting) from textual evidence without inflating or minimizing them. - Distinction Enforcement: Maintains critical separations such as use vs. authorship, causal contribution vs. intentional agency, and cognitive support vs. extended cognition. - Reflexive Testing: Applies structured tests including feedback-loop detection, counterfactual analysis, observer-loop assessment, and reflexive consistency checks. - Use Case: Given a philosophical essay about AI cognition that was drafted with AI assistance, the Skill classifies each AI contribution, evaluates the author's evaluative operations, and reports whether the work's claims about AI are consistent with how AI was actually used. ## Quick Start Analyze this manuscript's account of how AI was used during writing and assess whether that use creates reflexive consequences for its claims about authorship and cognition.
