opp-repl-smoke-tests — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited opp-repl-smoke-tests (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
Smoke tests are the minimum viable regression check: every selected simulation is launched briefly and its exit status is verified. A PASS means "it ran without crashing"; it does NOT imply correctness.
Upstream reference: https://github.com/omnetpp/opp_repl/blob/main/doc/smoke_tests.md
run_smoke_tests()
run_smoke_tests(simulation_project=aloha_project, config_filter="PureAlohaExperiment")
run_smoke_tests(sim_time_limit="1s")
Typical output:
[6/7] . -c TandemQueueExperiment -r 3 PASS [5/7] . -c TandemQueueExperiment -r 2 PASS ... Multiple smoke test results: PASS, summary: 7 PASS in 0:00:01.117562
Re-running after a change:
r = run_smoke_tests(simulation_project=aloha_project, config_filter="PureAlohaExperiment") r.rerun() # repeat everything r.get_fail_results().rerun() # only failures
opp_run_smoke_tests --load "~/workspace/omnetpp/*/.opp" -p fifo opp_run_smoke_tests -t 1s --filter PureAloha
run_all_tests() / run_release_tests().For deeper behavioral regressions, follow up with:
opp-repl-fingerprint-tests (trajectory-level).opp-repl-statistical-tests (scalar results).opp-repl-speed-tests (performance).opp-repl-chart-tests (rendered charts).crashing. Always layer with fingerprint or statistical tests.
sim_time_limit is critical: without it, a slow sample can turna smoke suite into an hour-long run. Upstream doesn't set a default -- pick 1s to 10s depending on model complexity.
simulation_config_filter=lambda c: not c.abstract semanticsis already the default; passing your own predicate overrides it.
opp-repl-running-simulations — underlying run machinery.opp-repl-tasks-and-results — inspecting test results.opp-repl-filtering — which configs to target.opp-repl-feature-and-release-tests — comprehensive suites.~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.