Audit and configure EDA toolchains for RTL design and verification.
npx skills add https://github.com/babyworm/rtl-agent-team --skill rat-setup
Please help me install this Agent Skill. Skill: rat-setup Source: https://github.com/babyworm/rtl-agent-team/tree/main/skills/rat-setup Command: npx skills add https://github.com/babyworm/rtl-agent-team --skill rat-setup
Ensures the local machine has the complete EDA toolchain and plugin configuration required for the RTL Agent Team pipeline so design and verification agents do not fail with tool-not-found or misconfiguration errors. It audits required, recommended, and optional tools, checks test infrastructure and commercial tool availability, and prevents wasted time troubleshooting environment issues.
Run the rat-setup skill to audit this machine, install missing EDA tools locally by default, and record the machine-wide environment configuration.
High-intent search queries and answers about installing and using this skill.
You can verify and install the EDA toolchain by running a parallel Bash-based audit that detects required, recommended, and optional tools like Verilator, cocotb, and SystemC, interactively remediating missing tools via local, global, or Docker fallback options.
To set up SystemC, cocotb, and Verilator, the skill audits your machine in parallel, categorizes these tools into required and recommended tiers, and interactively remediates missing components through local installs, global sudo commands, or a Docker fallback.
Docker is not strictly required to install Verilator and cocotb, as the setup process offers local installs and global sudo command suggestions first, using Docker only as an optional fallback for Tier 3 tooling if local installation is not feasible.
The best way to configure commercial EDA tool environments is to register their env_source entries during the interactive remediation phase, which verifies the sourcing commands and persists the configuration machine-wide in an env-config.json file.
The EDA toolchain setup persists environment configurations by writing a machine-wide env-config.json file and a setup completion marker, ensuring consistent RTL conventions and preventing tool-not-found errors across automated design and verification pipelines.
pacphiManage the VisionFlow container lifecycle and execute in-container commands via Docker socket.
babywormDefine Tier 4 integration test ordering and JSON result schemas for RTL pipelines.
ShenShan123Detect, install, and verify open-source EDA tools for RTL-to-GDS flows.
OpenHandsStart a Docker daemon and run containers inside containerized environments.
