analog-netlist-crawl

analog-netlist-crawl is a Physics, mathematics & simulation skill for AI agents, published by Arcadia-1 in the analog-agents repository on GitHub. Skillspace rates analog-netlist-crawl F (53/100) and it passed the safety scan; the rating is based on static analysis only.

Crawl and analyze post-layout parasitic netlists without running SPICE. Answers "what's the effective resistance from node A to node B across this massive R mesh?", "inside the VREFN mesh, which device pins are electrically farthest apart?", "which nets have the worst coupling?", "where does settling bottleneck?" — by parsing the netlist, building a sparse graph, and solving the resistance Laplacian / summing the capacitance network. Format-agnostic: Calibre xRC mr_pp (.pex.netlist), Spectre flat, Spectre with subckt + include chain (.pex / .pxi splits), and Cadence calibreview bundles all produce identical kernel output. TRIGGER whenever the user shares a post-layout / extracted / parasitic netlist and asks about symmetry, parasitic C, parasitic R, coupling, driving-point resistance, within-net R distribution, pin-to-pin R, SAR CDAC analysis, comparator input impedance — even if they don't say "post-layout". Also trigger on filenames ending in .pex.netlist, .pxi, or mentions of xRC,…

Grade

F

Quality

53 / 100

Safety

Passed

GitHub stars

41

Unproven: rated by static analysis only, not yet compared head-to-head.

Our two independent classifiers differ on this skill's category, so treat the placement as provisional.

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