ryanlewis’s gists

	{
	"allow": [
	"Bash(git status:*)",
	"Bash(git log:*)",
	"Bash(git diff:*)",
	"Bash(git show:*)",
	"Bash(git branch:*)",
	"Bash(git tag:*)",
	"Bash(git remote:*)",
	"Bash(git stash list:*)",

name	description	tools	model	color
cursor-code-orchestrator	Agent that uses GPT-5 (via cursor-agent) for analysis and problem identification (code review), then returns insights to Claude for safe code implementation. Use it for getting a code review for iterative improvement and to get final quality checks before a feature can be considered finalized.	Bash, Glob, Grep, Read, Edit	sonnet	purple

You are an elite AI orchestration specialist bridging Cursor and Claude for seamless code review and implementation workflows. Your expertise lies in coordinating multi-agent interactions to deliver comprehensive code analysis and actionable improvements.

Product Requirements Document: Figgo - Modern FIGlet Library for Go

Executive Summary

Product Vision

Build a high-performance, specification-compliant FIGlet text rendering library for Go that prioritizes production readiness, modern development practices, and developer experience.

Problem Statement

Existing Go FIGlet libraries suffer from:

Poor error handling (panic/fatal on invalid input)

Creating a PRD with AI Assistance: A Case Study

How we used AI to streamline Product Requirements Document creation for an MCP server proof of concept

Introduction

We all know that Product Requirements Documents (PRDs) are essential for any software project - they define expectations, technical specs, and success criteria. But let's be honest: creating comprehensive PRDs can be pretty time-consuming, especially when you're trying to make sure you haven't missed any technical details or edge cases.

This blog post walks through our real-world experience creating a PRD for an MCP (Model Context Protocol) dice roll server - a proof-of-concept project we needed to validate our organisation's adoption of MCP technology. What made this interesting was how we used AI assistance to speed up the whole process while keeping the quality high.

	const points = {
	'immortal': 7,
	'diamond': 6,
	'platinum': 5,
	'gold': 4,
	'silver': 3,
	'bronze': 2,
	'iron': 1,
	};

	-- Redis script to implement a leaky bucket
	-- see https://medium.com/callr-techblog/rate-limiting-for-distributed-systems-with-redis-and-lua-eeea745cb260
	-- (c) Florent CHAUVEAU <florent.chauveau@gmail.com>

	local ts = tonumber(ARGV[1])
	local cps = tonumber(ARGV[2])
	local key = KEYS[1]

	-- remove tokens < min (older than now() -1s)
	local min = ts -1

kubectl get rs,secrets -o json --namespace old | jq '.items[].metadata.namespace = "new"' | kubectl create-f -

	public class ContourFormRefreshPayload
	{
	public Guid Id { get; set; }
	}

	public class ContourFormCacheRefresher : JsonCacheRefresherBase<ContourFormCacheRefresher>
	{
	public static string Id = "AA2970FD-8785-42C2-A289-A7A6614CAE45";
	protected override ContourFormCacheRefresher Instance => this;
	public override Guid UniqueIdentifier => new Guid(Id);

	using System.Web.UI;
	using Examine;
	using Examine.LuceneEngine;
	using Examine.LuceneEngine.Providers;
	using Umbraco.Core;
	using Umbraco.Web;

	namespace AMAZINGWEBSITE.Web.Core.ApplicationEventHandlers
	{
	public class ConfigureLuceneIndexing : IApplicationEventHandler

	using System;
	using System.Linq;
	using System.Text.RegularExpressions;
	using System.Web;

	namespace MyUmbracoSite.Core.Extensions
	{
	public static class StringExtensions
	{
	// http://bendetat.com/the-greatest-string-formatwith-implementation-in-the-world.html