MongoDB Aggregation Pipeline Optimization
General MongoDB aggregation pipeline optimization techniques including early filtering, index usage, array operators vs $unwind, $lookup optimization, and performance debugging. Use when writing aggregation queries for ANY MongoDB project, debugging slow pipelines, or analyzing query performance. For M32RIMM-specific patterns, use mongodb-m32rimm-patterns skill.
telegram-bot-performance-engineer
This skill should be used when analyzing, profiling, or optimizing Telegram bots built with Python/Telethon, especially for performance bottlenecks, rate limits, caching, API usage, or when the user asks for a full repo review or best practices.
hook-audit
Audits Claude Code hooks for correctness, safety, and performance. Use when reviewing, validating, or debugging hooks, checking exit codes, error handling, or learning hook best practices.
ecto-query-analysis
Analyzes Ecto queries for N+1 problems, missing preloads, and performance issues.
memory-location
Configure chitta memory storage location for optimal I/O performance. Use when memory is slow, setting up fast storage, or moving the soul database.
postgresql-performance
Optimize PostgreSQL performance - EXPLAIN ANALYZE, indexing, query tuning
redis-performance
Master Redis performance - memory optimization, slow log analysis, benchmarking, monitoring, and tuning strategies
pr-reviewer
Review pull requests for quality, security, and performance. Use when user says "review my changes before I merge", "do a code review on this PR", "check if this is ready to merge", "review the diff for any issues", "give me feedback on these changes", or "is this PR ready for review".
