A curated collection of Agent Skills for working with PYXLL, to help AI agents write and understand code using the PyXLL Excel add-in.
99
90%
Does it follow best practices?
Impact
100%
1.56xAverage score across 17 eval scenarios
Advisory
Suggest reviewing before use
A financial analytics team uses a PyXLL-based Excel add-in to expose Python calculations directly in their spreadsheets. They need to add two new worksheet functions to their existing add-in:
portfolio_vol that accepts a 2D range of returns (rows = observations, columns = assets) and a 1D range of weights, and returns the portfolio volatility as a single float.compound_return that accepts an annual rate (float) and a number of compounding periods (integer), and returns the compound return factor.The team uses Python 3.10+ and numpy for numeric work. PyXLL is already installed and configured — the only deliverable is a new Python module to be loaded by the add-in.
Produce:
analytics.py — the Python module containing both functions, ready to be loaded by PyXLLdocs_consulted.md — a markdown file listing every PyXLL documentation URL you fetched, with a one-line note on what each page contributed to your implementation decisions