ordo-jit-optimization — engine ordo-jit-optimization, community, engine, ide skills, high-performance, rule-engine, rules-engine, Claude Code, Cursor, Windsurf

v1.0.0

关于此技能

适用于需要高级即时编译和模式感知直接内存访问以优化规则引擎执行的高性能代理。 Ordo JIT compilation and performance optimization guide. Includes Schema-aware JIT, TypedContext derive macro, Cranelift compilation, performance tuning. Use for optimizing rule execution performance, reducing latency, increasing throughput.

# 核心主题

Pama-Lee Pama-Lee
[24]
[2]
更新于: 3/10/2026

Killer-Skills Review

Decision support comes first. Repository text comes second.

Reference-Only Page Review Score: 4/11

This page remains useful for operators, but Killer-Skills treats it as reference material instead of a primary organic landing page.

Concrete use-case guidance Explicit limitations and caution
Review Score
4/11
Quality Score
44
Canonical Locale
en
Detected Body Locale
en

适用于需要高级即时编译和模式感知直接内存访问以优化规则引擎执行的高性能代理。 Ordo JIT compilation and performance optimization guide. Includes Schema-aware JIT, TypedContext derive macro, Cranelift compilation, performance tuning. Use for optimizing rule execution performance, reducing latency, increasing throughput.

核心价值

赋予代理使用基于Cranelift的JIT编译,利用模式感知直接内存访问和Expr AST实现20-30倍的性能改进,支持Rust开发和金融应用。

适用 Agent 类型

适用于需要高级即时编译和模式感知直接内存访问以优化规则引擎执行的高性能代理。

赋予的主要能力 · ordo-jit-optimization

使用JIT编译优化规则引擎性能
使用模式感知直接内存访问生成高性能金融模型
调试和优化Expr AST以提高执行效率

! 使用限制与门槛

  • 需要Rust编程语言
  • 依赖于Cranelift基于的JIT编译器
  • 模式感知直接内存访问是必需的以实现最佳性能

Why this page is reference-only

  • - Current locale does not satisfy the locale-governance contract.
  • - The page lacks a strong recommendation layer.
  • - The underlying skill quality score is below the review floor.

Source Boundary

The section below is supporting source material from the upstream repository. Use the Killer-Skills review above as the primary decision layer.

实验室 Demo

Browser Sandbox Environment

⚡️ Ready to unleash?

Experience this Agent in a zero-setup browser environment powered by WebContainers. No installation required.

Boot Container Sandbox

常见问题与安装步骤

以下问题与步骤与页面结构化数据保持一致,便于搜索引擎理解页面内容。

? FAQ

ordo-jit-optimization 是什么?

适用于需要高级即时编译和模式感知直接内存访问以优化规则引擎执行的高性能代理。 Ordo JIT compilation and performance optimization guide. Includes Schema-aware JIT, TypedContext derive macro, Cranelift compilation, performance tuning. Use for optimizing rule execution performance, reducing latency, increasing throughput.

如何安装 ordo-jit-optimization?

运行命令:npx killer-skills add Pama-Lee/Ordo/ordo-jit-optimization。支持 Cursor、Windsurf、VS Code、Claude Code 等 19+ IDE/Agent。

ordo-jit-optimization 适用于哪些场景?

典型场景包括:使用JIT编译优化规则引擎性能、使用模式感知直接内存访问生成高性能金融模型、调试和优化Expr AST以提高执行效率。

ordo-jit-optimization 支持哪些 IDE 或 Agent?

该技能兼容 Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer。可使用 Killer-Skills CLI 一条命令通用安装。

ordo-jit-optimization 有哪些限制?

需要Rust编程语言;依赖于Cranelift基于的JIT编译器;模式感知直接内存访问是必需的以实现最佳性能。

安装步骤

  1. 1. 打开终端

    在你的项目目录中打开终端或命令行。

  2. 2. 执行安装命令

    运行:npx killer-skills add Pama-Lee/Ordo/ordo-jit-optimization。CLI 会自动识别 IDE 或 AI Agent 并完成配置。

  3. 3. 开始使用技能

    ordo-jit-optimization 已启用,可立即在当前项目中调用。

! 参考页模式

此页面仍可作为安装与查阅参考,但 Killer-Skills 不再把它视为主要可索引落地页。请优先阅读上方评审结论,再决定是否继续查看上游仓库说明。

Imported Repository Instructions

The section below is supporting source material from the upstream repository. Use the Killer-Skills review above as the primary decision layer.

Supporting Evidence

ordo-jit-optimization

安装 ordo-jit-optimization,这是一款面向AI agent workflows and automation的 AI Agent Skill。支持 Claude Code、Cursor、Windsurf,一键安装。

SKILL.md
Readonly
Imported Repository Instructions
The section below is supporting source material from the upstream repository. Use the Killer-Skills review above as the primary decision layer.
Supporting Evidence

Ordo JIT Compilation and Performance Optimization

Schema-Aware JIT

Ordo's JIT compiler is based on Cranelift, supporting Schema-aware direct memory access with 20-30x performance improvement.

Core Architecture

                    ┌─────────────────┐
                    │   Expr AST      │
                    └────────┬────────┘
                             │
                    ┌────────▼────────┐
                    │ SchemaJITCompiler│
                    └────────┬────────┘
                             │
              ┌──────────────┼──────────────┐
              │              │              │
     ┌────────▼────────┐    │    ┌────────▼────────┐
     │  Field Offset   │    │    │  Native Code    │
     │   Resolution    │    │    │   Generation    │
     └─────────────────┘    │    └─────────────────┘
                    ┌───────▼────────┐
                    │ Machine Code   │
                    │ ldr d0, [ptr+N]│
                    └────────────────┘

TypedContext Derive Macro

rust
1use ordo_derive::TypedContext; 2 3#[derive(TypedContext)] 4struct UserContext { 5 age: i64, 6 balance: f64, 7 vip_level: i64, 8 #[typed_context(skip)] // Skip non-numeric fields 9 name: String, 10}

The generated Schema contains field offsets, JIT compiler directly generates memory load instructions.

Using JIT Evaluator

rust
1use ordo_core::expr::jit::{SchemaJITCompiler, SchemaJITEvaluator}; 2 3// Create compiler 4let mut compiler = SchemaJITCompiler::new()?; 5 6// Compile expression (with Schema) 7let schema = UserContext::schema(); 8let compiled = compiler.compile_with_schema(&expr, &schema)?; 9 10// Execute 11let ctx = UserContext { age: 25, balance: 1000.0, vip_level: 3 }; 12let result = unsafe { compiled.call_typed(&ctx)? };

Performance Comparison

MethodLatencyUse Case
Interpreter~1.63 µsDynamic rules, development/debugging
Bytecode VM~200 nsGeneral purpose
Schema JIT~50-80 nsHigh-frequency execution, fixed Schema

Optimization Strategies

1. Expression Pre-compilation

rust
1// Pre-compile expressions when loading rules 2let mut ruleset = RuleSet::from_json(json)?; 3ruleset.compile()?; // Pre-compile all expressions to bytecode 4 5// Or use one-step loading 6let ruleset = RuleSet::from_json_compiled(json)?;

2. Batch Execution

rust
1use ordo_core::prelude::*; 2 3let executor = RuleExecutor::new(); 4 5// Batch execution (reduces lock contention) 6let inputs: Vec<Value> = load_batch(); 7let results = executor.execute_batch(&ruleset, inputs)?;

3. Vectorized Evaluation

rust
1use ordo_core::expr::VectorizedEvaluator; 2 3let evaluator = VectorizedEvaluator::new(); 4let contexts: Vec<Context> = prepare_contexts(); 5let results = evaluator.eval_batch(&expr, &contexts)?;

4. Function Fast Path

Common functions (len, sum, max, min, abs, count, is_null) have inline fast paths, avoiding HashMap lookups.

Compiler Configuration

JIT Compiler Options

rust
1let mut compiler = SchemaJITCompiler::new()?; 2 3// View compilation statistics 4let stats = compiler.stats(); 5println!("Successful compiles: {}", stats.successful_compiles); 6println!("Total code size: {} bytes", stats.total_code_size);

Feature Flags

Configure in Cargo.toml:

toml
1[dependencies] 2ordo-core = { version = "0.2", features = ["jit"] } 3 4# Full features 5ordo-core = { version = "0.2", features = ["default"] } # jit + signature + derive

Note: JIT is not available on WASM targets (Cranelift doesn't support wasm32).

Performance Tuning Checklist

Compile-time Optimization

  • Build with --release mode
  • Enable LTO: lto = true
  • Set codegen-units = 1

Runtime Optimization

  • Pre-compile rule expressions
  • Use JIT for fixed Schema
  • Batch execution to reduce overhead
  • Set reasonable max_depth

Server Optimization

  • Set RUST_LOG=warn or info
  • Disable unnecessary tracing
  • Use connection pooling
  • Configure appropriate worker count

Benchmarking

Run built-in benchmarks:

bash
1# Basic benchmarks 2cargo bench --package ordo-core 3 4# JIT comparison tests 5cargo bench --package ordo-core --bench jit_comparison_bench 6 7# Schema JIT tests 8cargo bench --package ordo-core --bench schema_jit_bench

Typical Results (Apple Silicon)

expression/eval/simple_compare    time: [79.234 ns]
expression/eval/function_call     time: [211.45 ns]
rule/simple_ruleset              time: [1.6312 µs]
jit/schema_aware/numeric         time: [52.341 ns]

Key Files

  • crates/ordo-core/src/expr/jit/schema_compiler.rs - Schema JIT compiler
  • crates/ordo-core/src/expr/jit/schema_evaluator.rs - JIT evaluator
  • crates/ordo-core/src/expr/jit/typed_context.rs - Typed context
  • crates/ordo-derive/src/lib.rs - TypedContext derive macro
  • crates/ordo-core/benches/ - Benchmarks

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