I keep coming back to the same onboarding question: what happens in the first 10 minutes?
For agent tools, that window is brutal. A developer opens a repo, starts the agent, asks for a change, and waits to see if the tool understands the project. If the agent guesses the package manager, misses the test path, edits generated files, or asks the developer to explain the repo from scratch, trust drops fast.
That isn't an agent model problem every time. A lot of it is repo readiness.
The Agentic AI Foundation, hosted by the Linux Foundation, is building an open home for projects like MCP, goose, AGENTS.md, and agentgateway. That work can sound big and infrastructural, but one of the most useful entry points is small: make your repo easier for an agent to understand on the first run.
AGENTS.md is the repo-side context. goose is a practical runtime path. Together, they give you a way to move from "the agent is poking around" to "the agent made a useful first pass."
