How to add ANOVA one-way p-value to ggplot with ggsignif

I have the following data

library(tidyverse)
library(ggsignif)
set.seed(1)
a <- rnorm(n = 10, mean = 5, sd = 1)
b <- rnorm(n = 10, mean = 5.8, sd = 1)

data <- data.frame(label = c(rep("A", 10), rep("B", 10)), id = c(1:10, 1:10), 
                   value = c(a, b))

And I perform the one-way anova pot using this code:

a <- aov( value ~ label, data)
summary(a)

Which produces:

            Df Sum Sq Mean Sq F value Pr(>F)  
label        1  4.201   4.201   4.793  0.042 *
Residuals   18 15.779   0.877                 
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Notice the p-value is 0.042.

However when I tried with ggsignif with this code:

ggplot(data, aes(x = label, y = value )) + 
  geom_boxplot() + 
  geom_signif(comparison = list(c("A",  "B")), y_position = 11, test = function(a, b) {
    list(p.value = summary(aov(a ~ b))[[1]][["Pr(>F)"]][[1]])
  })

I got this:

Note the p-value stated there is 0.28 instead of 0.042. What's the right way to do it, so that I can put the 0.042 value inside the plot?