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Performance optimization guidelines for Splitrail. Use when optimizing parsing, reducing memory usage, or improving throughput.
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Guide for updating model pricing in Splitrail. Use when adding new AI model costs or updating existing pricing data.
Guide for working with Splitrail's MCP server. Use when adding tools, resources, or modifying the MCP interface.
Guide for adding a new AI coding agent analyzer to Splitrail. Use when implementing support for a new tool like Copilot, Cline, or similar.
Guide for Splitrail's terminal UI and file watching. Use when modifying the TUI, stats display, or real-time update logic.
Reference for Splitrail's core data types. Use when working with ConversationMessage, Stats, DailyStats, or other type definitions.
Basado en la clasificación ocupacional SOC
| name | performance |
| description | Performance optimization guidelines for Splitrail. Use when optimizing parsing, reducing memory usage, or improving throughput. |
futures::join_all() for concurrent stats loadingrayon for parallel iteration over filessimd_json exclusively for all JSON operations (note: rmcp crate re-exports serde_json for MCP server types)jwalk for parallel directory traversalSee existing analyzers in src/analyzers/ for usage patterns.
parking_lot locks over std::sync for better performanceBTreeMap for date-ordered data (sorted iteration)