dsh-binomial-pmf

In model-inference pipelines and statistical modeling workflows, computing the binomial probability mass function is a frequent yet low-level requirement: evaluating the probability of observing exactly k successes out of n independent Bernoulli trials. dsh-binomial-pmf was built precisely for that role—a lightweight, pure Node.js plugin that runs entirely offline with zero network dependencies, sparing you from pulling in a heavyweight scientific-computing library.\n\nThe core capability is deliberately focused: give it the number of trials n, the per-trial success probability p, and the observed success count k, and it hands back P(X = k) as a plain numeric result. There are no hidden side effects, no extra abstraction layers, and no configuration to wrestle with. When a reasoning step calls for a quick probability check, a confidence assessment, or a sampling validation, the zero-dependency, zero-config nature of this plugin keeps integration costs to a minimum.\n\nIt is well suited to developers running model inference on local or edge hardware who need offline probability math, as well as engineering teams that embed binomial-distribution checks into automated decision pipelines. If reaching for a bloated math library or firing off a network request for a single PMF call feels like overkill, this plugin is the lightest option on the shelf.