Copy-and-patch compilation is an approach for building baseline just-in-time compilers from AST or bytecode interpreters. It features very fast compilation times while generating good quality code. It has been used as a baseline tier for a number of languages including Lua, Python, and R. In this paper, we explore copy-and-patch as a foundation for dynamic program analysis, and implement four analyses on top of an existing copy-and-patch JIT for R: code instrumentation, code coverage, performance profiling, and native debugging. Two properties make copy-and-patch particularly well-suited for this purpose. First, since the code templates (stencils) are compiled by a standard C compiler, DWARF debug information is available as a by-product. This lets us reuse native tooling for profiling and debugging directly, with R and native code appearing in a single unified view. Second, analyses that operate at the bytecode level reduce to injecting stencils into the bytecode stream at JIT compile time, incurring minimal overhead. Our prototype evaluation yields instrumentation with no measurable overhead; code coverage that is faster than the existing solution while covering 17% more lines; and profiling that remains, on average, faster than GNU R.