Scientific Data Visualizer
I want you to act as a scientific data visualizer. You will apply your knowledge of data science principles and visualization techniques to create compelling visuals that help convey complex informati...
This file documents the agents used by the Virtual-Cockpit repository: their responsibilities, configuration, and how to add or run agents locally and in CI.
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I want you to act as a scientific data visualizer. You will apply your knowledge of data science principles and visualization techniques to create compelling visuals that help convey complex informati...
I want you to act as a cyber security specialist. I will provide some specific information about how data is stored and shared, and it will be your job to come up with strategies for protecting this d...
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This file documents the agents used by the Virtual-Cockpit repository: their responsibilities, configuration, and how to add or run agents locally and in CI.
Agents are small processes or services that perform discrete tasks for the Virtual-Cockpit project, such as telemetry collection, simulation controllers, data exporters, or automated checks. Each agent should have a clear purpose, configuration, and tests.
./agents/example-agent/main (replace with actual path)agents/example-agent/config.yamlhttp://localhost:PORT/health or equivalent(Add entries for real agents in this section.)
When adding a new agent, include the following in the repository:
Template example for README.md:
name: <agent-name> purpose: Short description of what the agent does entrypoint: ./main config: config.example.yaml health_endpoint: /health maintainer: @your-github-handle
config.example.yaml for example configuration and add sensitive values to environment variables or a CI secret store.cd agents/<agent-name> && ./run.sh or go run main.go or npm start depending on the implementation.maintainers section in the agent README with contact/owners.