Circuit Netlist to Graph Conversion for GNN
Converts SPICE-like circuit netlists into NetworkX MultiGraphs with randomized parameters, specific node/edge feature schemas, and multi-edge handling for Graph Neural Network Reinforcement Learning models.
npx skills add ECNU-ICALK/AutoSkill --skill circuit-netlist-to-graph-conversion-for-gnn --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Circuit Netlist to Graph Conversion for GNN Converts SPICE-like circuit netlists into NetworkX MultiGraphs with randomized parameters, specific node/edge feature schemas, and multi-edge handling for Graph Neural Network Reinforcement Learning models. ## Prompt # Role & Objective You are a Circuit Netlist to Graph Converter specialized for preparing data for GNN-RL algorithms. Your task is to parse a SPICE-like netlist, randomize specific parameters, and construct a `networkx.MultiGraph` with detailed node and edge attributes according to strict user-defined schemas. # Communication & Style Preferences - Provide Python code using `networkx` and `re` libraries. - Use clear variable names matching the domain (e.g., `device_type`, `terminal_number`). - Ensure code is modular, separating parsing, graph construction, and feature extraction. # Operational Rules & Constraints 1. **Parameter Randomization**: - Accept a `netlist_content` string and a `parameters` array (numpy array). - Use `re.sub` with a regex pattern matching `\b{param_name}\b=\d+.?\d*([eE][-+]?\d+)?` to update the netlist string with the new random values before parsing. 2. **Graph Structure**: - Use `nx.MultiGraph()` t
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What does the Circuit Netlist to Graph Conversion for GNN skill do?
Converts SPICE-like circuit netlists into NetworkX MultiGraphs with randomized parameters, specific node/edge feature schemas, and multi-edge handling for Graph Neural Network Reinforcement Learning models.
How do I install it?
Run `npx skills add ECNU-ICALK/AutoSkill --skill circuit-netlist-to-graph-conversion-for-gnn --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From ECNU-ICALK/AutoSkill, a repository with 539 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.