Here is a reprex of running library(tidyverse) as well as the sessionInfo. As you can see, the core packages are attached.
library(tidyverse)
sessionInfo()
#> R version 3.4.2 (2017-09-28)
#> Platform: x86_64-apple-darwin15.6.0 (64-bit)
#> Running under: macOS Sierra 10.12.6
#>
#> Matrix products: default
#> BLAS: /Library/Frameworks/R.framework/Versions/3.4/Resources/lib/libRblas.0.dylib
#> LAPACK: /Library/Frameworks/R.framework/Versions/3.4/Resources/lib/libRlapack.dylib
#>
#> locale:
#> [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
#>
#> attached base packages:
#> [1] stats graphics grDevices utils datasets methods base
#>
#> other attached packages:
#> [1] forcats_0.2.0 stringr_1.2.0 dplyr_0.7.4.9000
#> [4] purrr_0.2.4 readr_1.1.1.9000 tidyr_0.7.2
#> [7] tibble_1.3.4 ggplot2_2.2.1.9000 tidyverse_1.2.1
#>
#> loaded via a namespace (and not attached):
#> [1] Rcpp_0.12.14 cellranger_1.1.0 compiler_3.4.2
#> [4] plyr_1.8.4 bindr_0.1 tools_3.4.2
#> [7] digest_0.6.12 lubridate_1.7.1 jsonlite_1.5
#> [10] evaluate_0.10.1 nlme_3.1-131 gtable_0.2.0
#> [13] lattice_0.20-35 pkgconfig_2.0.1 rlang_0.1.4.9000
#> [16] psych_1.7.8 cli_1.0.0 yaml_2.1.16
#> [19] parallel_3.4.2 haven_1.1.0 bindrcpp_0.2
#> [22] xml2_1.1.9000 httr_1.3.1 knitr_1.17.20
#> [25] hms_0.4.0 rprojroot_1.2 grid_3.4.2
#> [28] tidyselect_0.2.3 glue_1.2.0.9000 R6_2.2.2
#> [31] readxl_1.0.0 foreign_0.8-69 rmarkdown_1.8
#> [34] modelr_0.1.1 reshape2_1.4.3 magrittr_1.5
#> [37] backports_1.1.2 scales_0.5.0.9000 htmltools_0.3.6
#> [40] rvest_0.3.2.9000 assertthat_0.2.0.9000 mnormt_1.5-5
#> [43] colorspace_1.3-2 stringi_1.1.6 lazyeval_0.2.1.9000
#> [46] munsell_0.4.3 broom_0.4.3 crayon_1.3.4
Created on 2017-12-15 by the reprex package (v0.1.1.9000).
The non-core members of the tidyverse are installed by
install.packages("tidyverse")
but are not attached. Though the "membership" has changed, you can read here for what makes tidyverse packages part of a coherent system.
Packages, such as cli (since you mentioned it), tidyselect, and crayon are part of what's called r-lib. While the tidyverse consists of highly-opinionated tools for data science; r-lib contains mostly-unopinionated infrastructure tools. Their specific uses differ, but, for the most part, r-lib packages are not something the average R user will need. They're more for development, testing, and are utilized by the tidyverse packages (e.g. tidyselect provides backend of functions like dplyr::select() or dplyr::pull() as well as several tidyr verbs) and other activities more akin to programming with R.