prompt-engineering

Open-source, bilingual AI video-prompt skill — rewrite ideas into model-ready text-to-video prompts. A portable Agent Skill (Claude Code, Codex, OpenClaw, Hermes); generate via Atlas Cloud — Seedance 2.0, Kling, Veo, Hailuo, Wan, Vidu, Gemini Omni, Grok Imagine.

Accelerating Long Context LLM Inference with Accuracy-Preserving Context Optimization in SGLang, vLLM, llama.cpp, OpenClaw, RAG, and Agentic AI.

An awesome list for collecting awesome lists related to AI.

Modular Prompting IDE - A lightweight web app allowing developers to componentize their prompt library for better, faster prompts.

Battle-tested skill library for AI agents. Save 98% of API costs with ready-to-use code for crypto, PDFs, search, web scraping & more. No trial-and-error, no expensive APIs.

Automatically completes the full workflow from requirement research → research review → planning → plan review → development → development review using → test AI large language models. Capable of autonomously handling medium to large-scale engineering projects.

Prompt Engineering Research Tool for AI APIs

GAN-style self-improvement loop for any text artifact: mutate, grade with a SEPARATE model, keep only verified wins (pairwise-judged), revert the rest. The git history is the improvement log.

CoordClaw: a multi-agent system that runs AI like a one-person company. Built on management & organizational theory — teams defined in natural language, collaboration driven by a message loop (not hard-coded DAGs). Auditable work logs, human god's-eye oversight.

A framework for human-readable prompt-based method with large language models. Specially designed for researchers. (Deprecated, check out LangChain for better usage!)

Ultimate Claude Fable 5 Guide 2026: Use Cases, Integrations & Benchmarks

Claude Code usage governor: compact professional output, context slimming, tool-output filtering, telemetry, and drift guardrails.

让 AI 主动记错题、自我迭代的协作机制 · A framework that makes your AI reflect on its own mistakes and stop repeating them

A curated collection of resources, papers, tools, and best practices for Context Engineering in AI agents and Large Language Models (LLMs).

LLM prompt language based on Jinja. Banks provides tools and functions to build prompts text and chat messages from generic blueprints. It allows attaching metadata to prompts to ease their management, and versioning is first-class citizen. Banks provides ways to store prompts on disk along with their metadata.

A complete collection of RAG interview questions, answers (548 questions & 41 RAG types), system design scenarios, architecture patterns, and production-ready concepts.

Goal-based planning and proof gate for AI coding agents

Claude Code Prompt Mechanism Visualizer — Electron desktop app

Visual knowledge bank for understanding large language models, with 180 concept cards from tokenization to deployment.

FACET (Feature‑Aware Contracted Extension for Text) is a human‑readable, machine‑deterministic markup language for AI prompting, orchestration, and tooling