The Discovery Problem: When AI Agents Build Tools No One Can Find
A case study on the discoverability of AI tools. 8 out of 15 skills were invisible to future agents.
In a single session, we installed 15 AI skills, but 8 were invisible to future agents. This case study highlights the gap between existing tools and their discoverability, emphasizing the need for self-auditing in multi-agent systems to prevent critical tools from being overlooked.
This synthesis was produced from its source by AI; there is no human editor or manual review step. How we work