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Babysitter benchmark-suite-manager

Manage benchmarks for algorithm engineering experiments and evaluations

install
source · Clone the upstream repo
git clone https://github.com/a5c-ai/babysitter
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/a5c-ai/babysitter "$T" && mkdir -p ~/.claude/skills && cp -r "$T/library/specializations/domains/science/computer-science/skills/benchmark-suite-manager" ~/.claude/skills/a5c-ai-babysitter-benchmark-suite-manager && rm -rf "$T"
manifest: library/specializations/domains/science/computer-science/skills/benchmark-suite-manager/SKILL.md
tags
#benchmark-management#algorithm-evaluation#experimentation#statistical-analysis#performance-comparison
source content

Benchmark Suite Manager

Purpose

Provides expert guidance on managing benchmark suites for algorithm engineering and experimental evaluation.

Capabilities

  • Standard benchmark suite access (DIMACS, TSPLIB, etc.)
  • Instance generation for specific problem classes
  • Statistical analysis of results
  • Performance comparison tables
  • Visualization of scaling behavior
  • Reproducibility support

Usage Guidelines

  1. Suite Selection: Choose appropriate benchmark suite
  2. Instance Selection: Select representative instances
  3. Execution: Run experiments systematically
  4. Analysis: Perform statistical analysis
  5. Reporting: Generate comparison tables and plots

Tools/Libraries

  • DIMACS
  • TSPLIB
  • SuiteSparse Matrix Collection
  • Statistical tools