index-tuner

Tune memory harness recall, decay-sweep, and write batching parameters.

Updated May 11, 2026
One-click install
npx skills add https://github.com/AesopScott/mojo --skill index-tuner
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: index-tuner
Source: https://github.com/AesopScott/mojo/tree/main/harnesses/skills/index-tuner
Command: npx skills add https://github.com/AesopScott/mojo --skill index-tuner

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill addresses performance bottlenecks in the Memory harness by providing a structured approach to tuning recall, decay, and batching parameters to ensure system responsiveness as data grows.

Core Features & Use Cases

  • Performance Tuning: Adjusts recall index, decay-sweep intervals, and write batching to maintain high throughput.
  • Harness Control: Provides a standardized runbook for inspecting and modifying the Memory harness boundary.
  • Use Case: When system latency increases due to a large memory footprint, use this Skill to systematically identify the bottleneck and apply a targeted configuration change to restore speed.

Quick Start

Use the index-tuner skill to inspect the current Memory harness configuration and propose a performance optimization for the recall index.

Frequently Asked Questions about index-tuner

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I reduce memory recall latency when my system dataset grows large?

To reduce recall latency, tune memory harness parameters like the recall index, decay-sweep intervals, and write batching to systematically target bottlenecks and restore system throughput as data grows.

What is memory write batching and how does it improve performance?

Memory write batching improves performance by grouping write operations to reduce processing overhead and latency, functioning as a tunable parameter within the memory harness to maintain high throughput for growing datasets.

How do I adjust decay-sweep intervals to optimize memory harness performance?

Adjust decay-sweep intervals by inspecting the current memory harness configuration and modifying the parameter boundaries, verifying changes through positive and boundary testing to ensure optimized responsiveness.

Can I use performance tuning to fix increasing latency in an existing memory management system?

Yes, performance tuning applies to existing memory management systems to fix increasing latency, providing a standardized runbook to inspect and modify the memory harness boundary safely without disruption.

What's the best way to safely tune memory recall index parameters?

The best way to tune recall index parameters safely is to follow defined safety protocols and verify configuration changes through positive and boundary testing before applying them to the live memory harness.

Why does memory recall latency increase when the memory footprint grows?

Memory recall latency increases with a growing footprint due to performance bottlenecks in the memory harness, requiring targeted tuning of recall, decay, and batching parameters to restore system responsiveness.