— · MIT
【EMNLP 2026 Demo】A debugging framework for agentic AI systems: diagnose failures, attribute root causes, recover with evidence, and validate fixes through reruns.
— · MIT
Runtime evidence that helps agents trace, profile, and burn down hotspots in application and native code, GPU kernels, and inference stacks.
v2.40.0 · Apache-2.0
📚 A zero-dependency, git-backed micro-lesson library for AI Agents to asynchronously share and search verified debugging experience. | https://misakanet.org
v1.3.37 · no license
Offline HarmonyOS NEXT developer skill library for AI coding assistants. Covers API 12–26 declarations, ArkTS/ArkUI, NDK, DevEco Studio, emulator automation, debugging, publishing, and reproducible local tooling.
v0.1.0 · no license
Superpowers skills for DeepSeek Harness: TDD, debugging, planning, and collaboration skills adapted from obra/superpowers
— · CC0-1.0
A meticulously curated list of useful plugins, extensions, tools and development resources built for DSH, covering productivity enhancement, functional expansion, debugging utilities and custom development modules.
— · no license
A collection of specialized agent skills for AI infrastructure development, enabling Claude Code to write, optimize, and debug high-performance systems.