A
licenseB
qualityD
maintenanceEnable any AI agent to forecast time-series data (e.g., sales, traffic) using Google's TimesFM or a zero-dependency statistical baseline.
3
Apache 2.0
skforecast-ai
Officialby skforecast
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TDQS
A3.6/5.0
Scored across 11 tools
Disambiguation4/5
Most tools have clearly distinct purposes: profile builds a profile, plan builds a plan, create_cv builds a CV strategy, and forecast/backtest/compare each run in distinct modes. The main risk is soft overlap between forecast, backtest, and compare (all execute a plan), but their outputs and semantics differ enough to distinguish them.
Naming Consistency4/5
Names are readable and mostly follow a verb_noun pattern (refine_plan, create_cv, get_code, get_failure, list_objects, describe_object), but several are bare verbs (forecast, backtest, compare, profile, plan), which is a minor deviation. No chaotic mixing of case or conventions.
Tool Count5/5
11 tools is well-scoped for a forecasting workflow server. Each tool maps to a distinct stage (profile, plan, CV, run, compare, inspect) and none feels redundant.
Completeness4/5
The lifecycle is largely covered: profile -> plan -> create_cv -> forecast/backtest/compare, plus inspection via list_objects, describe_object, get_code, and get_failure, and refinement via refine_plan. Minor gaps exist (no explicit cancel or delete tool despite mentions of cancellation and object storage), but agents can work around these.
Maintenance
ActivityActive
ResponsivenessUnresponsive