Lindy 性能调优

v20260311

lindy-performance-tuning

指导如何诊断并提升 Lindy AI 代理执行速度，通过合并步骤、缓存上下文和并行处理来降低延迟、提升吞吐。

Lindy 性能调优延迟吞吐自动化代理可靠性

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概览

Lindy AI Performance Tuning

Overview

Optimize Lindy AI agent execution speed and reliability. Lindy agents run as multi-step automations where each step (LLM call, tool execution, API call) adds latency.

Prerequisites

Lindy workspace with active agents
Access to agent configuration and run history
Understanding of agent step execution flow

Instructions

Step 1: Identify Slow Steps

Step 2: Consolidate LLM Steps

Step 3: Cache Agent Context Data

Step 4: Parallelize Independent Steps

Step 5: Optimize Trigger Configuration

For detailed implementation code and configurations, load the reference guide: Read(${CLAUDE_SKILL_DIR}/references/implementation-guide.md)

Error Handling

Issue	Cause	Solution
Agent timeout (>60s)	Too many sequential steps	Consolidate steps, add parallel execution
Step retry loop	Transient API failure	Set max retries to 2, add fallback step
Slow LLM step	Prompt too long or complex	Shorten prompt, use focused instructions
High run frequency	Trigger firing too often	Add filters to trigger configuration

Examples

Basic usage: Apply lindy performance tuning to a standard project setup with default configuration options.

Advanced scenario: Customize lindy performance tuning for production environments with multiple constraints and team-specific requirements.

Output

Configuration files or code changes applied to the project
Validation report confirming correct implementation
Summary of changes made and their rationale

See ORM implementation details for output format specifications.

Resources

Official ORM documentation
Community best practices and patterns
Related skills in this plugin pack

信息

Category 编程开发

Name lindy-performance-tuning

版本 v20260311

大小 3.62KB

Source jeremylongshore/claude-code-plugins-plus-skills

更新时间 2026-03-12