I use GitHub Copilot CLI for practical development work: understanding unfamiliar code, reviewing changes, generating tests, and debugging from the terminal. After writing my beginner’s guide to GitHub Copilot CLI, I wanted to test a harder question:
Can a coding assistant diagnose an AI-agent failure from structured execution evidence instead of a wall of logs?
This matters to me as a full-stack developer working with Next.js, TypeScript, MERN applications, and AI features across the broader TheCampusCoders ecosystem. A coding assistant can read source code, but an agent failure often depends on the path taken at runtime: which tool ran, what happened between retrieval and generation, and whether a technically successful run produced the expected behavior.
For this experiment, I connected AgentInspect to GitHub Copilot CLI through AgentInspect’s read-only MCP server. I used a controlled, keyless TypeScript fixture so that the same failure could be reproduced without an API key or a nondeterministic model response.
Disclosure: I tested AgentInspect independently for the workflow described here. The maintainer reviewed the commands for technical accuracy; the conclusions are my own. @agent-inspect/mcp-server was in Preview when I ran this experiment.
