Low-curvature skill fixed-point conjecture for LASKO systems

Let $\mathcal{A}\to\mathsf{WfMd}$ be a Lie algebroid of controlled intervention modes over a typed Markdown workflow space, with anchor $\rho:\mathcal{A}\to T\mathsf{WfMd}$. For controlled edit sections $s_i,s_j\in\Gamma(\mathcal{A})$, let $R_{\mathrm{Md}}(i,j)$ denote the visible edit nonclosure residual, $R_{\mathrm{ker}}(i,j)$ the kernel interaction residual, and $R_{\mathrm{DB}}(i,j)$ the path-dependent reverse-blame curvature; let $R_\mathcal{A}$ be the curvature of a chosen connection on $\mathcal{A}$. Let $\Phi$ be the combined forward rollout, reverse critique, and edit-selection operator of a LASKO system on a typed Markdown tangent category. Low-curvature skill fixed-point conjecture. Under compactness, continuity, and bounded-edit assumptions appropriate to a chosen edit theory, locally optimal stable skills occur at fixed points of $\Phi$ where the task gradient, visible IC residual, kernel interaction residual, DB curvature, and algebroid connection curvature vanish relative to the observation functor. This proposes a geometric fixed-point characterization of stable skill optimization: stability should coincide with the simultaneous disappearance of task and causal-curvature signals, including visible edit nonclosure, hidden procedural interactions, reverse-blame path dependence, and connection curvature. The statement is conditional on assumptions that are not formalized more precisely in the source, and its general validity is not established.