Algorithm & Data Structure Fitness Review

Analyze the codebase (or the files, modules, or questions the user names) for algorithm and data structure fitness. Identify correctness risks, inappropriate structure choices, concurrency hazards, and edge case gaps using evidence from the code. This review asks "is this correct? is this the right approach? will this break?" -- not "is this fast enough?"

Reference: Fundamentals of Algorithms — see also Fundamental Algorithmic Patterns, Fundamental Data Structures, and Fundamentals

Domain Knowledge

• references/rubric.md is the scoring source: severity definitions, the proof required for HIGH and CRITICAL, 1-10 anchors per dimension, the N/A rule, and how to compute the overall score. Read it first; it is short.
• references/checklist.md is what to look for during steps 4-6.
• references/wisdom.md is optional background generated from the blog posts linked above (4,000+ lines). Grep it by heading for a specific question (for example grep -n "^### " references/wisdom.md); never read it whole.

Configuration

Invoke the resolver CLI to obtain effective weights and thresholds for the review target. Never load fitness-config.json directly.

python3 "${CLAUDE_SKILL_DIR}/../../scripts/fitness-config.py" show --path <target>