Runs a comprehensive diagnostic suite for common CRAN submission issues that are not caught by standard R CMD check. Like a doctor for your package, this function examines your code, DESCRIPTION file, documentation, general package structure, and CRAN policy compliance to identify potential problems that could cause CRAN submission delays or rejections.
Arguments
- path
Character. Path to the R package directory. Defaults to current directory (
".").- verbose
Logical. Whether to print detailed diagnostic output to console. Defaults to
getOption("checktor.verbose", TRUE).- progress
Logical. Whether to show progress bars during diagnostics. Defaults to
getOption("checktor.progress", verbose).
Value
A checktor_results object (list) containing:
code_issues: Results from code diagnosticsdescription_issues: Results from DESCRIPTION file diagnosticsdocumentation_issues: Results from documentation diagnosticsgeneral_issues: Results from general package diagnosticspolicy_issues: Results from CRAN policy violation diagnosticsmetadata: List with package path, diagnosis time, total issue count, total failed-check count, and checktor version
Each diagnostic category contains a passed element showing which individual
checks passed/failed, plus detailed results for each check.
Details
The function runs five categories of diagnostics: Code, DESCRIPTION,
Documentation, General, and Policy. See diagnose_code_issues(),
diagnose_description_issues(), diagnose_documentation_issues(),
diagnose_general_issues(), and diagnose_policy_violations() for the
specific checks within each category.
The metadata$total_issues figure counts the total number of distinct
issues found across all checks (e.g., 80 lines using T/F count as 80,
not 1). The metadata$failed_checks figure counts how many individual
checks reported any issue at all.
See also
health_report() to generate detailed reports, prescribe() for treatment
recommendations, checkup() for quick health checks
Examples
# Run against a synthetic package with known T/F issues
pkg <- example_diagnose_scenario("code_examples/tf_usage_bad.R",
show_content = FALSE)
results <- checktor(pkg, verbose = FALSE, progress = FALSE)
results # the diagnosis summary
#> ── Package Doctor - Diagnosis Summary ──────────────────────────────────────────
#> Patient: examplepackage
#> Examined: 2026-06-26 20:38:18.849831
#> Doctor version: 0.1.0
#>
#> CODE ISSUES: 1 failing check
#> DESCRIPTION ISSUES: 3 failing checks
#> DOCUMENTATION ISSUES: HEALTHY
#> GENERAL ISSUES: HEALTHY
#> POLICY ISSUES: HEALTHY
#>
#> ! Overall health: NEEDS ATTENTION (10 issues)
#> Run `summary()`, `issues()`, or `prescribe()` for details
summary(results) # per-category overview
#> category checks passed failed issues
#> 1 code 13 12 1 7
#> 2 description 16 13 3 3
#> 3 documentation 8 8 0 0
#> 4 general 4 4 0 0
#> 5 policy 4 4 0 0
issues(results) # every issue as a tidy data frame
#> category check file line
#> 1 code tf_usage tf_usage_bad.R 8
#> 2 code tf_usage tf_usage_bad.R 11
#> 3 code tf_usage tf_usage_bad.R 15
#> 4 code tf_usage tf_usage_bad.R 18
#> 5 code tf_usage tf_usage_bad.R 22
#> 6 code tf_usage tf_usage_bad.R 23
#> 7 code tf_usage tf_usage_bad.R 26
#> 8 description license <NA> NA
#> 9 description cph_role <NA> NA
#> 10 description description_length <NA> NA
#> location
#> 1 tf_usage_bad.R:8
#> 2 tf_usage_bad.R:11
#> 3 tf_usage_bad.R:15
#> 4 tf_usage_bad.R:18
#> 5 tf_usage_bad.R:22
#> 6 tf_usage_bad.R:23
#> 7 tf_usage_bad.R:26
#> 8 MIT/BSD license requires '+ file LICENSE' for copyright holders
#> 9 Authors@R lacks any [cph] (copyright holder) role
#> 10 Description too short: 1 sentences, 18 words
#> message
#> 1 T/F usage check
#> 2 T/F usage check
#> 3 T/F usage check
#> 4 T/F usage check
#> 5 T/F usage check
#> 6 T/F usage check
#> 7 T/F usage check
#> 8 License check
#> 9 cph role check
#> 10 Description length check
is_healthy(results) # FALSE
#> [1] FALSE