diff --git a/base/compiler/abstractinterpretation.jl b/base/compiler/abstractinterpretation.jl
index b3e18a6ee7..fc8e2d1aee 100644
--- a/base/compiler/abstractinterpretation.jl
+++ b/base/compiler/abstractinterpretation.jl
@@ -547,6 +547,8 @@ function abstract_call_method(interp::AbstractInterpreter, method::Method, @nosp
         return MethodCallResult(Any, false, false, nothing, Effects())
     end
 
+    @show sig
+
     # Limit argument type tuple growth of functions:
     # look through the parents list to see if there's a call to the same method
     # and from the same method.

julia> using Revise

julia> Revise.track(Core.Compiler)

julia> using Cthulhu

julia> @descend optimize=false sin(1.0)
[snip]
sin(x::T) where T<:Union{Float32, Float64} @ Base.Math special/trig.jl:29

julia> Core.eval(Cthulhu, quote
       function do_typeinf!(interp::AbstractInterpreter, mi::MethodInstance)
           result = InferenceResult(mi)
           # we may want to handle the case when `InferenceState(...)` returns `nothing`,
           # which indicates code generation of a `@generated` has been failed,
           # and show it in the UI in some way ?
           # branch on https://github.com/JuliaLang/julia/pull/42082
           frame = @static hasmethod(InferenceState, (InferenceResult,Symbol,AbstractInterpreter)) ?
                   InferenceState(result, #=cache=# :global, interp)::InferenceState :
                   InferenceState(result, #=cached=# true, interp)::InferenceState
           CC.typeinf(interp, frame)
           return nothing
       end
       end)

julia> @descend optimize=false sin(1.);
:sig = Tuple{typeof(Base.abs), Float64}
:sig = Tuple{Type{Float64}, Base.Irrational{:π}}
:sig = Tuple{typeof(Base.:(/)), Float64, Int64}
:sig = Tuple{typeof(Base.promote), Float64, Int64}
:sig = Tuple{typeof(Base._promote), Float64, Int64}