backtesting-configuration

backtesting-configuration is a Time series & forecasting skill for AI agents, published by skforecast in the skforecast repository on GitHub. Skillspace rates backtesting-configuration D (59/100) and it passed the safety scan; the rating is based on static analysis only.

Configures TimeSeriesFold parameters for backtesting based on deployment scenarios. Maps business requirements (retraining frequency, forecast horizon, data budget) to cross-validation strategy parameters. Use when the user describes how they plan to deploy or evaluate a model.

Grade
D
Quality
59 / 100
Safety
Passed
GitHub stars
1,512

Unproven: rated by static analysis only, not yet compared head-to-head.

This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.

Our review

Architecture
84 / 100
Maturity
Basic: a single SKILL.md
Security scan
No issues found
License
BSD-3-Clause
Adoption
Adopted by 1 other repositories, in 0 collections
Scope
Vendor-specific: built around one product. Configures skforecast TimeSeriesFold backtesting parameters

Not checked yet

  • Not judged on the rubric yet (not a contender in its category)
  • No blind task eval yet
  • Sibling files (scripts, references) not fetched; security scan covers SKILL.md only

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