pastas
pastas is a Time series & forecasting skill for AI agents, published by SteadfastAsArt in the geoscience-skills repository on GitHub. Skillspace rates pastas B (82/100) and it passed the safety scan; the rating is based on static analysis only.
Groundwater time series analysis and modelling using transfer function noise models. Use when Claude needs to: (1) Analyze groundwater level time series, (2) Model well responses to precipitation/pumping, (3) Calibrate aquifer parameters from head data, (4) Forecast or hindcast groundwater levels, (5) Decompose hydrological signals into components, (6) Compare response functions, (7) Perform model diagnostics and uncertainty analysis.
- Grade
- B
- Quality
- 82 / 100
- Safety
- Passed
- GitHub stars
- 40
Unproven: rated by static analysis only, not yet compared head-to-head.
Our two independent classifiers differ on this skill's category, so treat the placement as provisional.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 79 / 100
- Maturity
- Packaged: licensed, with a version or references
- Security scan
- No issues found
- License
- MIT
- Adoption
- Adopted by 0 other repositories, in 1 collections
- Scope
- Vendor-specific: built around one product. How to use the public Pastas groundwater modelling library
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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