fory-performance-optimization
Run profile-driven bottleneck optimization across Apache Fory implementations (Java, C++, Python/Cython, Go, Rust, Swift, C#, JavaScript/TypeScript, Dart, Kotlin, Scala). Use when improving serialize/deserialize throughput or latency, recovering regressions against a reference commit, diagnosing flamegraphs, fixing perf-related CI failures, or porting proven optimizations across languages without protocol or API regressions.
tsa-find
Fast file + content search with code-aware sizing. Replaces Read/Grep/find for routine "where is this file" / "grep for X" / "show me lines 10-20 of Y" questions. Returns file paths + line numbers + a sized chunk, not the whole file. Use when: - "Find files matching <pattern>" / "show me all *.yml under config/" - "Grep for 'TODO' / 'FIXME' / 'TODO\\(perf\\)' / regex anywhere" - "How big is <file>" / "is this file too large to read fully" - "Show me lines 50-80 of <file>" / "read just the relevant slice" - "Find all files matching name + containing string" Replaces: native find + grep + cat invocations (~3-10k tokens for big repos) with single MCP calls (200-500 tokens).
diffusion-perf
Deprecated alias (merged into diffusion-kernel).
ai-agent-bench
Use when the user wants to benchmark or compare AI agents (Claude Code, Codex, OpenCode) on a refactoring, perf, or code-change task in the current repo. Use when user says compare agents, benchmark Claude vs Codex, agent eval, measure agent, AI agent comparison, agent trial, /ai-agent-bench.
Io.Github.Perf AI/Perf Mcp
Fact-check and fix AI outputs. Hallucination detection, schema validation, auto-repair.
Io.Github.Rog0x/Perf
Benchmark, memory, Big O analysis for AI agents
benchmark
Run scalex performance benchmarks, profiling, and timing analysis. Use this skill whenever the user asks to benchmark scalex, measure performance, profile index/query times, compare before/after performance of a change, investigate bottlenecks, or mentions "benchmark", "perf", "how fast", "timing", "hyperfine", "profile", "flame graph", "profiling", "--timings", "slow", "bottleneck", "regression", "memory", "heap", "GC", "allocation". Also use proactively after implementing performance improvements to verify gains. Covers 6 layers: built-in --timings, hyperfine benchmarks, async-profiler flame graphs, JFR recording, microbenchmarks, and memory profiling.