opp-repl-overview — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited opp-repl-overview (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.
opp_repl replaces ad-hoc shell loops and Qtenv clicking with reproducible, scriptable workflows for OMNeT++. Same feature set, three interfaces:
opp_repl) — interactive Python with allhelpers pre-loaded.
opp_build_project,opp_run_simulations, opp_run_*_tests, opp_update_*_test_results) — for CI and scripts.
endpoint (a Unix-socket stdio bridge for local clients like Claude Code, or a TCP+token endpoint for remote ones).
...install opp_repl. -> opp-repl-installation
...create a NEW OMNeT++ project from scratch (write files, build, run). -> opp-repl-project-scaffolding (← START HERE for "make a new simulation", "create a new model", "build an example from zero"). On current opp_repl this is ONE function call: create_project(name, path=..., namespace=False). -> then opp-repl-running-simulations -> then opp-repl-result-analysis to read the numbers out (on current opp_repl: r.get_scalars() on the result). -> keep opp-repl-troubleshooting on hand; new projects hit §4 of that skill on namespace/package mismatches.
...run simulations that already exist. -> opp-repl-running-simulations + opp-repl-filtering -> opp-repl-tasks-and-results for drill-down / rerun -> opp-repl-result-analysis for reading the numbers.
...regression-test my project. Pick the type:
opp-repl-smoke-tests — it ran, it didn't crash.opp-repl-fingerprint-tests — behavior hasn't drifted.opp-repl-statistical-tests — scalar results in tolerance.opp-repl-speed-tests — CPU instr. count stable.opp-repl-chart-tests — analysis charts unchanged.opp-repl-module-image-tests — module/network rendering unchanged.opp-repl-sanitizer-tests — ASAN/UBSan clean.opp-repl-feature-and-release-tests — comprehensive suites.All test skills cross-reference opp-repl-running-simulations and opp-repl-tasks-and-results.
...compare / bisect / debug a regression. -> opp-repl-comparing-simulations + opp-repl-fingerprint-tests -> opp-repl-tasks-and-results for post-mortem inspection.
...tune a parameter to match a target. -> opp-repl-parameter-optimization + opp-repl-running-simulations.
...measure speed / cost. -> opp-repl-profiling (call-stack profiles) or opp-repl-speed-tests (regression) or opp-repl-coverage-reports (line coverage).
...distribute runs across multiple machines. -> opp-repl-ssh-cluster + opp-repl-running-simulations.
...read .sca / .vec result files after a run. -> opp-repl-result-analysis (includes a bundled script).
...debug a build or run failure. -> opp-repl-troubleshooting FIRST — it maps every common symptom ("Building X failed", exit 127, "Class not found", etc.) to its exact cause and fix.
...wire opp_repl into an AI agent / MCP client. -> opp-repl-mcp-server (stdio bridge over a Unix socket, or TCP+token) + opp-repl-ai-workflows.
...let a human (in a terminal) and the AI share ONE live REPL. -> opp-repl-shared-terminal (tmux + MCP, same namespace).
...isolate the agent's `execute_python` under bubblewrap. -> opp-repl-sandbox.
...set up CI on GitHub. -> opp-repl-cli-tools + opp-repl-github-actions.
...use a specific opp_env-managed OMNeT++ version (e.g. omnetpp-6.3.0 + inet-4.6.0). -> opp-repl-opp-env-integration + opp-repl-opp-files.
| Capability | Skill |
|---|---|
| Install / setenv | opp-repl-installation |
| Core object model | opp-repl-concepts |
.opp descriptors | opp-repl-opp-files |
| NEW project from zero | opp-repl-project-scaffolding |
| Interactive REPL usage | opp-repl-repl-usage |
| Shell wrappers for CI | opp-repl-cli-tools |
| Build + run simulations | opp-repl-running-simulations |
| Filtering configs/runs | opp-repl-filtering |
| Task & result model | opp-repl-tasks-and-results |
| Read .sca / .vec | opp-repl-result-analysis |
| Error decoder | opp-repl-troubleshooting |
| Smoke tests | opp-repl-smoke-tests |
| Fingerprint tests | opp-repl-fingerprint-tests |
| Statistical tests | opp-repl-statistical-tests |
| Speed tests | opp-repl-speed-tests |
| Chart tests | opp-repl-chart-tests |
| Module-image tests | opp-repl-module-image-tests |
| Sanitizer tests | opp-repl-sanitizer-tests |
| Feature + release tests | opp-repl-feature-and-release-tests |
| Comparing simulations | opp-repl-comparing-simulations |
| Parameter optimization | opp-repl-parameter-optimization |
| Coverage reports | opp-repl-coverage-reports |
| Profiling (perf/Hotspot) | opp-repl-profiling |
| Overlay builds | opp-repl-overlay-builds |
| SSH / Dask cluster runs | opp-repl-ssh-cluster |
| GitHub Actions dispatch | opp-repl-github-actions |
| opp_env integration | opp-repl-opp-env-integration |
| MCP server for AI agents | opp-repl-mcp-server |
| Shared human+AI REPL | opp-repl-shared-terminal |
| Sandboxed execution | opp-repl-sandbox |
| End-to-end AI recipes | opp-repl-ai-workflows |
Three high-value APIs on current opp_repl (Apr 2026+) that the skills route you to:
create_project(name, path=..., namespace=False) — scaffold anew project in one call. See opp-repl-project-scaffolding.
build_project(simulation_project=p) — builds. Auto-generatesthe Makefile from .oppbuildspec on the first call.
r.get_scalars() / r.get_vectors() / r.get_histograms() —read results into a pandas DataFrame directly from a SimulationTaskResult or MultipleSimulationTaskResults.
If you're not sure what to load, start with this core set — it covers 80% of real-world opp_repl usage:
opp-repl-concepts (object model) opp-repl-opp-files (project descriptors) opp-repl-running-simulations (the main entry point) opp-repl-tasks-and-results (inspecting what happened) opp-repl-result-analysis (reading .sca files) opp-repl-troubleshooting (decoding errors)
Add one or two test-type skills when testing, or opp-repl-mcp-server when connecting an agent.
opp_run or the OMNeT++ IDE is simpler..sca files with no rerun — just useopp_scavetool directly.
opp_repl is headless.
distils.
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.