Loading skill
Install any skill in seconds. Free to start, no credit card required.
Get Started Free →waybarrios/codeql
Scans a codebase for security vulnerabilities using CodeQL's interprocedural data flow and taint tracking analysis.
Passed 12 of 20 test cases with the skill, and 5 of 20 without it.
and 9 more in the full report
9 fixed4 passed either way8 still failing1 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 9 test cases the skill fixed. Same model, same prompt, with and without the skill.
After selecting query packs (such as official packs, Trail of Bits, or Community packs) for our analysis run, where should the record of selected rulesets be documented within the output directory?
| Checked | Without skill | With skill |
|---|---|---|
| Logs the list of selected query packs to rulesets.txt inside the output directory. | Missed | Passed |
The instructions your model reads when the skill loads.
Supported languages: Python, JavaScript/TypeScript, Go, Java/Kotlin, C/C++, C#, Ruby, Swift.
Skill resources: Reference files and templates are located at references/ and workflows/.
Database quality is non-negotiable. A database that builds is not automatically good. Always run quality assessment (file counts, baseline LoC, extractor errors) and compare against expected source files. A cached build produces zero useful extraction.
Data extensions catch what CodeQL misses. Even projects using standard frameworks (Django, Spring, Express) have custom wrappers around database calls, request parsing, or shell execution. Skipping the create-data-extensions workflow means missing vulnerabilities in project-specific code paths.
Explicit suite references prevent silent query dropping. Never pass pack names directly to codeql database analyze — each pack's defaultSuiteFile applies hidden filters that can produce zero results. Always generate a custom .qls suite file.
Zero findings needs investigation, not celebration. Zero results can indicate poor database quality, missing models, wrong query packs, or silent suite filtering. Investigate before reporting clean.
macOS Apple Silicon requires workarounds for compiled languages. Exit code 137 is arm64e/arm64 mismatch, not a build failure. Try Homebrew arm64 tools or Rosetta before falling back to build-mode=none.
Follow workflows step by step. Once a workflow is selected, execute it step by step without skipping phases. Each phase gates the next — skipping quality assessment or data extensions leads to incomplete analysis.
All generated files (database, build logs, diagnostics, extensions, results) are stored in a single output directory.
OUTPUT_DIR../static_analysis_codeql_1. If that already exists, increment to _2, _3, etc.In both cases, always create the directory with mkdir -p before writing any files.
# Resolve output directory
if [ -n "$USER_SPECIFIED_DIR" ]; then
OUTPUT_DIR="$USER_SPECIFIED_DIR"
else
BASE="static_analysis_codeql"
N=1
while [ -e "${BASE}_${N}" ]; do
N=$((N + 1))
done
OUTPUT_DIR="${BASE}_${N}"
test cases passed, vs 5 / 20 without
Published skills whose descriptions closely match this one, with their headline benchmark lift.
More skills from the same source and nearby in the registry, with their headline benchmark lift.