timeseries-recursive-multistep-forecasting
timeseries-recursive-multistep-forecasting is a Time series & forecasting skill for AI agents, published by wenmin-wu in the ds-skills repository on GitHub. Skillspace rates timeseries-recursive-multistep-forecasting D (65/100) and it passed the safety scan; the rating is based on static analysis only.
Forecast a multi-step horizon by predicting one day ahead, writing the prediction back into the panel as the new "actual", recomputing all lag and rolling features that depend on it, then predicting the next day — turns a one-step LightGBM regressor into a 28-day forecaster without changing the model
- Grade
- D
- Quality
- 65 / 100
- Safety
- Passed
- GitHub stars
- 52
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
- 94 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- Not declared. Check the repository before reusing it.
- Adoption
- Adopted by 0 other repositories, in 1 collections
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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