bgauryy

Claude Code Internal Tools - Technical Reference

Complete technical documentation of Claude Code's internal tools

This document provides comprehensive technical details about Claude Code's internal tools, including parameter schemas, implementation behaviors, and usage patterns.

Claude Sonnet 4.5

Technical Details:

Next.js Server Components Architecture

Deep Dive Analysis: Complete flow from routing to rendering

Source: Next.js repository (vercel/next.js)
Analysis Date: October 15, 2025

Deep Agents Planning Document

Building Next-Generation Multi-Agent AI Systems

🎯 Executive Summary

This document outlines the comprehensive planning approach for building Deep Agents - sophisticated multi-agent AI systems that combine planning, specialized sub-agents, persistent memory, and coordinated intelligence to solve complex, real-world problems.

Key Innovation: Moving from simple tool-using chatbots to autonomous, collaborative agent ecosystems that can handle enterprise-level tasks with human-like planning and execution capabilities.

Deep Agents Context Document

Technical Architecture and Implementation Guide

🔍 Concrete Example: Company Research Agent

Based on the research conducted using Octocode MCP, here's a real-world example of Deep Agents in action:

Guy Hartstein's Company Research Agent

React Compiler Function Memoization Analysis

Document Version: 1.0
Date: 7/27/25
Issue Reference: React Issue #34014
Research Tool: octocode-mcp

Executive Summary

The React Compiler exhibits conservative behavior when optimizing function calls returned from custom hooks, leading to missed memoization opportunities. Functions that are referentially stable and return deterministic values are not automatically memoized, requiring manual useMemo wrapping to achieve optimization. This document provides a comprehensive technical analysis of the root cause, current implementation details, and potential solutions.

MCP Explained by OctoCode MCP: Deep Dive and Comparison of Popular Code Search & Documentation MCPs (Context7, GitHub Official MCP, AWS MCP Suite)

About This Analysis

This research was conducted entirely using OctoCode MCP on July 21, 2025, to gather all MCP platform details, codebase data, and technical specifications. OctoCode MCP analyzed multiple MCP servers (including itself) by retrieving live data from GitHub repositories, npm packages, documentation, and API endpoints to create this comprehensive comparison.

What This Demonstrates:

Self-Referential Analysis: OctoCode MCP analyzing itself and competitors
Cross-Repository Research: Analysis spanning multiple codebases and ecosystems
Real-Time Intelligence: Live data gathering from GitHub, npm, and package registries with verified accuracy

	# AI Agent Chat Application - Implementation Plan

	## Research Summary

	### Repositories Analyzed
	- langchain-ai/langgraphjs-gen-ui-examples (347⭐) - LangGraph.js agent examples
	- assistant-ui/assistant-ui (6,896⭐) - TypeScript/React AI chat UI library
	- FlowiseAI/Flowise (46,168⭐) - Visual AI agent builder with LangChain
	- CopilotKit/CopilotKit (24,685⭐) - React UI + infrastructure for AI agents

	import { encode as toonEncoder } from '@byjohann/toon'
	import { createByEncoderName } from '@microsoft/tiktokenizer'
	import { writeFileSync, mkdirSync } from 'fs'
	import { join } from 'path'

	async function main() {
	const data = {};

	// Generate large dataset programmatically
	const emails = ['john.doe', 'jane.smith', 'bob.wilson', 'alice.johnson', 'charlie.brown', 'david.miller', 'emma.davis', 'frank.garcia', 'grace.martinez', 'henry.rodriguez'];

	<!--
	This is an example for HTML generation using octocode-mcp with this prompt:
	https://github.com/bgauryy/octocode-mcp
	"use octocode
	Search for threejs examples
	get top examples from top repositories
	create a stunning, hyper-realistic video of a man walking through a futuristic city. be creative! blow my mind!"
	-->

	<!DOCTYPE html>

	---
	description: Senior engineer process for systematic code changes
	alwaysApply: true
	---

	You are a senior software engineer. Follow this process before making any changes:

	1. Validate the clarity and feasibility of the request.
	2. Suggest refinements if needed — do not modify code yet.
	3. Analyze how the change affects logic, structure, or flow.