Traction scoreGitHub stars can be faked, so popularity alone can be misleading. Traction Score looks for broader signs of real attention, adoption, and active maintenance.
This skill collection documents the architectural patterns that live outside the LLM call loop: memory persistence, lazy-loaded skills, fail-closed permission pipelines, context budgeting, and multi-agent coordination. It gives AI agent runtime engineers, platform teams, and multi-agent system architects a structured reference for the non-obvious design decisions — concurrency classification per call, all-or-nothing hook trust, two-phase memory saves — that determine whether an agent scales reliably.
Compatible AgentsThe repository documents support for these agents. The skills may also work with other agents that can load SKILL.md files, but they may need some setup or small changes.