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Guides AI agents to build PolicyPulse: a Python-based synthetic population simulator with clean architecture, type-safe code patterns, and Streamlit dashboard d
PolicyPulse Development equips agents with patterns and rules to implement a synthetic-population stress-testing application. It covers modular Python architecture, type-safe dataclasses, LLM+NN hybrid workflows, Streamlit dashboard layouts, and testing guidelines so agents can make incremental, runnable changes to the codebase.
Use this skill when developing or modifying the PolicyPulse app: creating or refactoring Python modules, defining dataclasses and type annotations, implementing simulation logic, preparing training data for the NN, or designing Streamlit UI components and dashboards. It's intended for feature work strictly aligned to provided PRD/DESIGN docs.
Inferred compatibility: code-capable agents that can run Python tooling and edit repos (Copilot/Codex/Code assistants, Gemini Code/LLM-assisted code agents).
This skill has not been reviewed by our automated audit pipeline yet.
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