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Guidance for building PolicyPulse — a synthetic-population simulation dashboard with clean architecture, strong Python typing, and Streamlit UI patterns.
This skill provides detailed implementation and architectural guidance for PolicyPulse: a synthetic population simulator and analytics dashboard. It prescribes clean architecture, dataclass-first data models, type-safe Python patterns, Streamlit UI layout conventions, testing patterns, and operational constraints.
Use this skill when developing or reviewing the PolicyPulse project: writing business logic, creating Streamlit UI components, defining dataclasses, or implementing NN model training and evaluation. It's also suitable when enforcing project constraints (no DBs, file-based persistence, Plotly for charts).
Best for developer-assistant agents that generate code and follow architecture constraints (e.g., Codex, Claude Code, OpenClaw).
PolicyPulse Development is a development-guide skill for building a synthetic-population policy simulation dashboard using Streamlit, scikit-learn, and Google Gemini LLM. The SKILL.md is comprehensive with clean architecture principles, type-safety guidelines, and UI design patterns. No scripts were bundled in the skill package for testing. The repo contains shell scripts and Python source, but these weren't registered as skill scripts. The skill is narrowly scoped to one specific application, limiting its broader usefulness.
Well-written development guide but extremely niche — only useful for building the PolicyPulse app itself. Architecture score reflects lack of skill-spec compliance (no scripts/ or references/ directories, monolithic SKILL.md). Source path 'policy-reader_01' in DB doesn't match actual repo path 'PolicyPulse Development-2', suggesting the skill was queued from a now-deleted or renamed path.
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