Unresolved binaries are common in spectroscopic surveys, and their blended light biases the parameters inferred for them. Methods to detect them exist, but applying one to a new data release is limited mostly by operating know-how that is rarely written down. We package the double-lined spectroscopic binary decomposition of El-Badry et al. (2018b) for reuse on APOGEE spectra, with the executable operations as nine tool servers built on the Model Context Protocol (MCP) and the operating decisions as a Skill. Run over the 238,205 DR19 dwarfs under a fixed driver script, the classifier flags 41,466 SB2 candidates, about fifteen times the 2,645 identified in DR13, though not at matched purity. The 8.1% control false-positive rate implies that close to 40% are single stars, so we release the sample as a candidate list. The joint visit fit prefers two stars for 46% of the SB2 with multiple visits. Of these, 4,149 have velocity changes above 10 km/s. This cut is also passed by 7% of flagged single stars. The pipeline velocities identify another 3,943 velocity variables. We compare the eccentricities of the best-sampled binaries and find no significant difference between the close twins (q > 0.95) and matched non-twins, which excludes an eccentricity excess of the kind measured at wide separations. An ablation of two operating decisions illustrates that a fresh agent recovers a removed decision only when its absence leaves a measurable trace in the fit. We release the tools, the Skill, and the DR19 catalog with its multi-epoch supplement.

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