guard-cache

Cache guard evaluations to reduce latency in safety-critical system boundaries.

Updated May 11, 2026

Search Tags:#performance #caching #optimization #safety #latency #harness

Ready to run

npx skills add https://github.com/AesopScott/mojo --skill guard-cache

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: guard-cache
Source: https://github.com/AesopScott/mojo/tree/main/harnesses/skills/guard-cache
Command: npx skills add https://github.com/AesopScott/mojo --skill guard-cache

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill addresses latency and throughput bottlenecks in safety-critical systems by caching guard evaluations, preventing redundant processing of known safe patterns.

Core Features & Use Cases

Performance Optimization: Reduces system friction by memoizing guard results for repeated, safe requests.
Safety Boundary Control: Provides a structured runbook for modifying safety enforcement rules without compromising system integrity.
Use Case: When a specific API route experiences high latency due to repeated safety checks on identical, safe payloads, use this skill to implement a cache layer that accelerates throughput while maintaining strict safety compliance.

Quick Start

Use the guard-cache skill to inspect the current Safety performance boundary and propose a caching strategy for the identified bottleneck.

Frequently Asked Questions about guard-cache

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

FAQPage Schema

How do I reduce latency caused by repeated safety checks on identical API payloads?▼

Reduce latency by caching guard evaluations to prevent redundant processing of known safe patterns. This memoizes guard results for repeated requests, accelerating throughput while maintaining strict safety compliance for high-traffic routes.

What is guard evaluation caching and how does it optimize safety harness performance?▼

Guard evaluation caching is a technique that memoizes safety check results to optimize safety harness performance. It prevents redundant processing of known safe requests, systematically reducing latency bottlenecks in safety-critical system boundaries.

How do I implement a cache layer for safety enforcement rules without compromising system integrity?▼

Implement a cache layer by inspecting the current safety performance boundary and proposing a targeted caching strategy. Use a structured runbook to modify enforcement rules while validating cache-driven behavior changes against existing safety rules.

Can I use caching to optimize policy enforcement and request filtering workflows?▼

Yes, caching optimizes policy enforcement and request filtering workflows by memoizing guard results. This reduces system friction and improves throughput for repeated, safe payloads without altering the underlying safety boundary controls.

What are the limitations of caching guard evaluations in safety-critical systems?▼

The primary limitation is ensuring cache-driven behavior changes do not bypass existing safety rules. Systematic identification of performance bottlenecks and continuous validation against safety boundaries are required to prevent stale cache entries from compromising integrity.