performance

Performance optimization guidelines for Splitrail. Use when optimizing parsing, reducing memory usage, or improving throughput.

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Repository: Piebald-AI/splitrail
Last source activity: January 1, 2026 at 00:15
Detected SKILL.md language: English
Stars: 219
Forks: 25

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name	performance
description	Performance optimization guidelines for Splitrail. Use when optimizing parsing, reducing memory usage, or improving throughput.

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

Prefer parallel processing for I/O-bound operations
Use parking_lot locks over std::sync for better performance
Avoid loading all messages into memory when not needed
Use BTreeMap for date-ordered data (sorted iteration)

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name	performance
description	Performance optimization guidelines for Splitrail. Use when optimizing parsing, reducing memory usage, or improving throughput.

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

Prefer parallel processing for I/O-bound operations
Use parking_lot locks over std::sync for better performance
Avoid loading all messages into memory when not needed
Use BTreeMap for date-ordered data (sorted iteration)

performance

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Review the source files

Performance Considerations

Techniques Used

Guidelines

More from this repository

Performance Considerations

Techniques Used

Guidelines

More from this repository