What are the principles we can use to build LLM-powered software that is actually good enough to put in the hands of production customers?

[ICML'24 Spotlight] LLM Maybe LongLM: Self-Extend LLM Context Window Without Tuning

A discovery and compression tool for your Python codebase. Creates a knowledge graph for a LLM context window, efficiently outlining your project | Code structure visualization | LLM Context Window Efficiency | Static analysis for AI | Large Language Model tooling #LLM #AI #Python #CodeAnalysis #ContextWindow #DeveloperTools

Documentation snippets for LLM context injection

A local-first memory layer for AI (Cursor, Zed, Claude). Persistent architectural context via semantic search.

Transform and optimize your markdown documentation for Large Language Models (LLMs) and RAG systems. Generate llms.txt automatically.

Building Agents with LLM structured generation (BAML), MCP Tools, and 12-Factor Agents principles

A lightweight tool to optimize your C# project for LLM context windows by using a knowledge graph | Code structure visualization | Static analysis for AI | Large Language Model tooling | .NET ecosystem support #LLM #AI #CSharp #DotNet #CodeAnalysis #ContextWindow #DeveloperTools

[ICLR 2025] Official code repository for "TULIP: Token-length Upgraded CLIP"

A discovery and compression tool for your Java codebase. Creates a knowledge graph for a LLM context window, efficiently outlining your project #LLM #AI #Java #CodeAnalysis #ContextWindow #DeveloperTools #StaticAnalysis #CodeVisualization

Smart code context extractor for AI assistants

🚀 Intelligent Claude Code status line with multi-provider AI support, real-time token counting, and universal model compatibility. Supports Claude (Sonnet 4: 1M, 3.5: 200K), OpenAI (GPT-4.1: 1M, 4o: 128K), Gemini (1.5 Pro: 2M, 2.x: 1M), and xAI Grok (3: 1M, 4: 256K) with verified 2025 context limits.

Information on LLM models, context window token limit, output token limit, pricing and more.

Token Oriented Object Notation (TOON) for Linked Data

Turns your local codebase into a secure, token-optimized context prompt for LLMs like ChatGPT and Claude.

A visualization website for comparing LLMs' long context comprehension based on the FictionLiveBench benchmark.

Context-optimized MCP server for web scraping. Reduces LLM token usage by 70-90% through server-side CSS filtering and HTML-to-markdown conversion.

A tool that analyzes your content to determine if you need a RAG pipeline or if modern language models can handle your text directly. It compares your content's token requirements against model context windows to help you make an informed architectural decision.

MCP Bridge - 99% context reduction for AI agents. Consolidates multiple MCP servers behind lazy-loading meta-tools. Result compaction, schema caching, health checks.

Give Claude Code photographic memory in ONE portable file. No database, no SQLite, no ChromaDB - just a single .mv2 file you can git commit, scp, or share. Native Rust core with sub-ms operations.