diff --git a/src/find.jl b/src/find.jl
index ab15843..300c24a 100755
--- a/src/find.jl
+++ b/src/find.jl
@@ -1,37 +1,50 @@
 """
-    findmax(s::AbstractString, itr, dist::StringDistance; min_score = 0.0)
+    findmax(s::AbstractString, itr, dist::StringDistance; min_score = 0.0) -> (x, index)
 
 `findmax` returns the value and index of the element of `itr` that has the 
 highest similarity score with `s` according to the distance `dist`. 
 It returns `(nothing, nothing)` if none of the elements has a similarity score 
-higher or equal to `min_score` (default to 0.0)
+higher or equal to `min_score` (default to 0.0).
 The function is optimized for `Levenshtein` and `DamerauLevenshtein` distances 
-(potentially modified by `Partial`, `TokenSort`, `TokenSet`, or `TokenMax`)
+(as well as their modifications via `Partial`, `TokenSort`, `TokenSet`, or `TokenMax`).
 """
 function Base.findmax(s::AbstractString, itr, dist::StringDistance; min_score = 0.0)
-    vmin = Threads.Atomic{typeof(min_score)}(min_score)
-    vs = [0.0 for _ in 1:Threads.nthreads()]
+    min_score = Threads.Atomic{typeof(min_score)}(min_score)
+    scores = [0.0 for _ in 1:Threads.nthreads()]
     is = [0 for _ in 1:Threads.nthreads()]
     Threads.@threads for i in collect(keys(itr))
-        v = compare(s, itr[i], dist; min_score = vmin[])
-        v_old = Threads.atomic_max!(vmin, v)
-        if v >= v_old
-            vs[Threads.threadid()] = v
+        score = compare(s, itr[i], dist; min_score = min_score[])
+        score_old = Threads.atomic_max!(min_score, score)
+        if score >= score_old
+            scores[Threads.threadid()] = score
             is[Threads.threadid()] = i
         end
     end
-    imax = is[argmax(vs)]
+    imax = is[argmax(scores)]
     imax == 0 ? (nothing, nothing) : (itr[imax], imax)
 end
+"""
+    argmax(s::AbstractString, itr, dist::StringDistance; min_score = 0.0)
 
+`argmax` returns the index of the element of `itr` that has the 
+highest similarity score with `s` according to the distance `dist`. 
+It returns `nothing` if none of the elements has a similarity score 
+higher or equal to `min_score` (default to 0.0).
+The function is optimized for `Levenshtein` and `DamerauLevenshtein` distances 
+(potentially modified by `Partial`, `TokenSort`, `TokenSet`, or `TokenMax`)
+"""
+function Base.argmax(s::AbstractString, itr, dist::StringDistance; min_score = 0.0)
+    findmax(s, itr, dist; min_score = min_score)[2]
+end
 
 """
     findall(s::AbstractString, itr, dist::StringDistance; min_score = 0.8)
     
 `findall` returns the vector of indices for elements of `itr` that have a 
-similarity score higher or equal than `min_score` according to the distance `dist`. 
+similarity score higher or equal than `min_score` according to the distance `dist`.
+If there are no such elements, return an empty array. 
 The function is optimized for `Levenshtein` and `DamerauLevenshtein` distances 
-(potentially modified by `Partial`, `TokenSort`, `TokenSet`, or `TokenMax`)
+(as well as their modifications via `Partial`, `TokenSort`, `TokenSet`, or `TokenMax`).
 """
 function Base.findall(s::AbstractString, itr, dist::StringDistance; min_score = 0.8)
     out = [Int[] for _ in 1:Threads.nthreads()]