LLMOps · Eval

It corrals 500+ news feeds and dozens of data streams into one dashboard so you can monitor geopolitical, financial, and infrastructure signals without sending everything to a cloud LLM.

It builds a persistent structural map of your codebase so AI assistants read only the files in a change's blast radius instead of the whole repo.

This curriculum closes the gap between calling AI APIs and understanding the loss curves underneath.

It is an open-source bridge between large language models and the instant messaging apps you already tolerate.

gstack turns Claude Code into a structured engineering team so a single founder can ship like a twenty-person startup without writing most of the code.

Because verbose AI explanations waste tokens and patience, this skill makes agents talk like cavemen—terse, accurate, and cheap.

Headroom sits between your agents and the LLM to compress tool outputs, logs, and RAG chunks, delivering the same answers with a fraction of the tokens.

A local-first, Rust-built AI agent that connects to 15-plus LLM providers and 70-plus tools, now governed by the Linux Foundation instead of a single company.

It exists because pure vector search often misses the big picture, so LightRAG auto-maps entities and relationships into a knowledge graph for richer retrieval.

Graphiti continuously ingests structured and unstructured data into temporal context graphs so agents can query what is true now—or was true at any specific moment—without rebuilding the graph from scratch.

Impeccable exists to stop AI coding assistants from defaulting to the same handful of SaaS-template tells—Inter everywhere, nested cards, purple gradients—by giving them a curated design vocabulary and 27 deterministic anti-pattern rules.

Mastra gives TypeScript developers a full-stack toolkit for building autonomous AI agents and workflows, bundling model routing, memory, evals, and observability into a single framework.

An AI job-search filter that scores listings, tailors your CV per role, and tracks the pipeline so you only apply to jobs worth keeping.

A terminal tool that scores hundreds of local LLMs against your actual hardware so you stop downloading models that won't fit.

It strips the telltale signs of AI-generated writing from text, replacing statistical blandness with prose that sounds like it came from a person.

GraphRAG exists to give LLMs a structured memory layer for reasoning over messy, private narrative text.

Because stitching together LLM workflows, RAG, agents, and observability by hand is a full-time job.

Sub2API pools AI subscriptions behind a metered gateway so teams or resellers can distribute API quotas without building their own billing stack.

Quivr wraps retrieval-augmented generation in a Python library with YAML-configurable workflows, letting you swap LLMs and vector stores without rewriting plumbing.

n8n gives technical teams visual workflow automation without trapping them in a GUI when they need JavaScript, Python, or npm packages.