Composable agent skills for driving OMNeT++ simulations via opp_repl, compatible with Claude and Windsurf.
opp_repl-skill is easy to set up with trust notes worth reviewing. Check agent compatibility and use-case fit before adding it to your workflow.
npx skills add tabgab/opp_repl-skillRun the command in your terminal.
Confirm that the skill files were added to your agent workspace.
Check the README requirements before invoking the skill in your agent.
This is a collection of skill files that help AI agents like Claude or Windsurf control OMNeT++ network simulations through the opp_repl tool. Each skill covers a specific task, such as creating projects, running simulations, or analyzing results. They are designed to be easy to combine and use together.
This repository provides a composable pack of Agent Skills for opp_repl, an interactive Python REPL and CLI tool for OMNeT++ simulations. The skills follow the Anthropic Agent Skills format (SKILL.md with YAML frontmatter) and are designed to be portable, composable, and progressively disclosed. They work with Claude Desktop, Claude Code, Windsurf, and any SKILL.md-aware agent. The pack includes 26 skills covering foundations (overview, project scaffolding, running simulations, result analysis, troubleshooting), AI workflows (MCP integration, shell-driven workflows), and reference materials (USAGE_EXAMPLES.md, TROUBLESHOOTING.md, VERIFICATION.md). Skills reference each other via 'See also' headings, enabling agents to load the right context on demand. The repository also includes installation guides for Windsurf and verification logs proving the pack works on stock OMNeT++ with numerical results within 3.2% of analytical reference.
Looks usable, but maintenance, license, or security notes deserve a closer look.
Last commit was about 41 days ago.
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No license detected; review before production use.
Automate OMNeT++ simulation setup, execution, and result analysis using AI agents.
Create new OMNeT++ projects from scratch with correct build configuration.
Troubleshoot common simulation errors like exit 127 or class not found.
Run regression tests by comparing simulation outputs against expected values.
Integrate opp_repl with MCP servers for agent-driven simulation workflows.
Agent skills can change coding-agent behavior; review every SKILL.md and referenced script before installing.
Check shell, network, file-system, credential, and API-key requirements before running skill workflows.
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