Give neural_attractor and neural_reversible a machine metadata field and eval_all skip entries, so python src/eval_all.py variants/ skips them cleanly instead of erroring (it scores fitness variants and skips standalone machines by that field). README sync: list both new machines in the variant table, intro, and repository layout; correct the standalone-machine count (5->7), the eval_all skip count (four->seven), and the universal-constructor family round-trip (23->26 files, 551->971 MB, both new files codec-verified byte-identical).

neural_attractor: tighten the README section and module docstring to a plain technical description (energy form, gate gadgets, clamped-subset modes, exactness and NP-hardness of the search modes)

neural_attractor: an energy-based threshold computer where computation is relaxation to a ground state and the program is the coupling matrix. No program counter, no clock, no forward-only execution: clamp any subset of wires and relax. AND/OR/NOT energy gadgets (each zero iff the gate relation holds) make it universal by construction; forward evaluation is exact, and clamping outputs runs circuits backward (an 8x8 multiplier compiled to couplings factors 35=5x7, 143=11x13) or solves SAT. Module, tests, artifact builder, and the shipped coupling matrix.