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Piebald-AI

performance

by Piebald-AI

Fast, cross-platform, real-time token usage tracker and cost monitor for Gemini CLI / Claude Code / Codex CLI / Qwen Code / Cline / Roo Code / Kilo Code / GitHub Copilot / OpenCode / Pi Agent / Piebald.

⭐ 91🍴 9📅 Jan 23, 2026
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SKILL.md

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

  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)

Score

Total Score

75/100

Based on repository quality metrics

✓SKILL.md

SKILL.mdファイルが含まれている

+20
✓LICENSE

ライセンスが設定されている

+10
✓説明文

100文字以上の説明がある

+10
○人気

GitHub Stars 100以上

0/15
✓最近の活動

1ヶ月以内に更新

+10
○フォーク

10回以上フォークされている

0/5
✓Issue管理

オープンIssueが50未満

+5
✓言語

プログラミング言語が設定されている

+5
✓タグ

1つ以上のタグが設定されている

+5

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