LLMOps · Eval

It stops long-running agents from drifting by forcing them to verify progress through independent roles before every new round.

SAGE scores whether an A2A agent should keep a task, recruit complementary teammates, or hand it off entirely—then updates its beliefs from execution evidence.

It wraps DeepSeek Harness in a Tauri shell so you can skip the Node.js, pnpm, and Docker chores entirely.

Because coding agents will force-push to main or leak API keys unless something stops them mid-flight.

It exists to give retail A-share traders a lightweight, self-hosted alternative to bloated commercial terminals—no forced cloud data, no pretend AI stock picks.

A plugin and skin pack that turns the DeepSeek Harness Web UI into a skinnable, pet-equipped control center.

It spares tech transfer offices the weeks of manual patent, market, and literature review needed to assess a paper's commercial potential.

It treats documentation as a batch pipeline: point it at a repo and it emits a README, logo, structure map, and MkDocs wiki—local models optional.

fenic offloads inference-heavy context work into a declarative DataFrame pipeline, then serves the results to any agent framework as bounded, typed tools.

Graft writes a plain-English map of your codebase into linked markdown files so coding agents stop burning tokens rediscovering what they learned last session.

It exists because most RAG tutorials end at 'hello vector DB,' while production requires query routing, evidence budgets, and circuit breakers.

Memmy exists so switching between Cursor, Claude Code, and Codex doesn't mean starting your project history from scratch.

ReachAI exists because Dify and friends are built for greenfield AI apps, not for wiring agents into existing Java ERP systems that already own the business logic.

This project exists because AI-generated Chinese is fluently anonymous, so it encodes hard editorial rules and a prose linter to force models to write with the specific gravity of a real person.

Tracely converts real production agent failures into hermetic, zero-cost regression tests that block pull requests before they ship the same bug twice.

OpenKB compiles raw documents into a persistent, interlinked wiki so knowledge accumulates instead of being re-derived on every query.

Hyperresearch turns Claude Code into a tiered, multi-agent research pipeline that persists every source in a searchable, compounding vault.

GoModel exists to spare you from juggling a dozen LLM API formats by unifying them behind a single OpenAI-compatible endpoint written in Go.

Infrastructure to evaluate and improve agents in reproducible, stateful environments at scale.

These prompts exist because treating ChatGPT like a magic template machine is why your user stories still sound like Mad Libs.