# Performance > Performance optimization guidelines for Splitrail. Use when optimizing parsing, reducing memory usage, or improving throughput. Use when this capability is needed. - Skill: `tomevault-io/performance-5` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add tomevault-io/performance-5` - Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/performance-5/raw - Safety review: pending (external: skill-scanner PASS, skillspector PASS) - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Coding & Dev Tools - Author: tomevault-io (https://skillmd.com/u/tomevault-io) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/tomevault-io/performance-5 --- # Performance Considerations ## Techniques Used - **Parallel analyzer loading** - `futures::join_all()` for concurrent stats loading - **Parallel file parsing** - `rayon` for parallel iteration over files - **Fast JSON parsing** - `simd_json` exclusively for all JSON operations (note: `rmcp` crate re-exports `serde_json` for MCP server types) - **Fast directory walking** - `jwalk` for parallel directory traversal - **Lazy message loading** - TUI loads messages on-demand for session view See existing analyzers in `src/analyzers/` for usage patterns. ## Guidelines 1. Prefer parallel processing for I/O-bound operations 2. Use `parking_lot` locks over `std::sync` for better performance 3. Avoid loading all messages into memory when not needed 4. Use `BTreeMap` for date-ordered data (sorted iteration) --- > Converted and distributed by [TomeVault](https://tomevault.io/claim/piebald-ai) — claim your Tome and manage your conversions.