Skill-Usage

Harbor framework for agent evaluation. Use when: (1) Running harbor commands (harbor run, harbor tasks check), (2) Creating/validating SkillsBench tasks, (3) Understanding task format or debugging failures.

Discovers relevant agent skills using keyword (BM25) search. Breaks complex tasks into sub-tasks and finds 10 skills via term matching. Use when starting a new task, looking for specialized capabilities, or wanting to find best practices for a domain.

Discovers relevant agent skills using semantic (embedding) search. Breaks complex tasks into sub-tasks and finds 10 skills via natural language similarity. Use when starting a new task, looking for specialized capabilities, or wanting to find best practices for a domain.

Discovers relevant agent skills from a local index of skills for a given task. Breaks complex tasks into sub-tasks and finds 10 skills across keyword, semantic, and hybrid search. Use when starting a new task, looking for specialized capabilities, or wanting to find best practices for a domain.

Civilization 6 district mechanics library. Use when working with district placement validation, adjacency bonus calculations, or understanding Civ6 game rules.

Three.js scene-graph parsing and export workflows for mesh baking, InstancedMesh expansion, part partitioning, per-link OBJ export, and URDF articulation.

Clean messy tabular datasets with deduplication, missing value imputation, outlier handling, and text processing. Use when dealing with dirty data that has duplicates, nulls, or inconsistent formatting.

Difference-in-Differences causal analysis to identify demographic drivers of behavioral changes with p-value significance testing. Use for event effects, A/B testing, or policy evaluation.

Engineer dataset features before ML or Causal Inference. Methods include encoding categorical variables, scaling numerics, creating interactions, and selecting relevant features.

Detect anomalies in time series data using Prophet Framework (Meta), which frames the seasonality, trend holiday effect and other needed regressors into its model, to identify unusual surges or slumps in trends. This is a general methodology analyst can use for understanding what changes of their tracking metrics are manifesting anomalies pattern.

Recovering missing spreadsheet values by using totals, percentages, growth rates, and other mathematical constraints in tabular data.