Performance

Performance is a Quality skill for Claude Code, published by Piebald-AI in splitrail.

217 stars25 forkson Piebald-AI/splitrailAdded 2026/09/04Repository updated 2026/09/03

agenticanalyzerantigravity-cliblazing-fastccusageclaude-codeclinecodexgcusagekilo-codeopencodepi-agentpiebaldqwenqwen-coderavishingrustsplitrailusagezoo-code

Install in seconds

Install Performance

Copy Performance into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.

terminal

npx degit https://github.com/Piebald-AI/splitrail/tree/main/.claude/skills/performance ~/.claude/skills/performance

Requires Node.js. Downloads this skill only — not the rest of the repository — into your Claude Code skills folder.

Without Node.js

git clone https://github.com/Piebald-AI/splitrail.git

Clones the whole repository, then copy the skill’s own directory into your skills folder yourself.

In this catalog

Source file: .claude/skills/performance/SKILL.md in Piebald-AI/splitrail
Installs to: ~/.claude/skills/performance
Collection: One of 6 skills cataloged from this repository
Category: Quality — 1557 skills

What Performance does

Performance provides guidelines for optimizing Splitrail code. Use it when improving parsing, reducing memory usage, or increasing throughput.

Performance is cataloged under Quality on DirSkills. Performance comes from a repository tagged agentic, analyzer, antigravity-cli, blazing-fast and ccusage.

Documentation

README

Excerpt

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

This is the opening of the README. Read the full README on GitHub.

Frequently asked about Performance

What else does Piebald-AI publish alongside Performance?
Performance is one of 6 skills that DirSkills catalogs from Piebald-AI/splitrail, the repository it ships in. Its siblings there include New Analyzer, Pricing and Splitrail MCP. Each one is a separate skill with its own page in this directory, installs the same way Performance does, and is maintained by Piebald-AI in that same repository. The rest of the collection is listed on the Piebald-AI/splitrail page.
How does Performance compare to other Quality skills?
Performance ranks #1401 by stars among the 1557 Quality skills in this catalog. The most-starred ones next to it are Benchmark, Benchmark Optimization Loop and API Design Patterns. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of Performance against them. Open each page to compare what they document and how they install.