Everything below is public and can be checked on GitHub or kobiton.com.
- Customer
- Kobiton, a real-device testing cloud for mobile apps. A paid engagement, April to June 2026.
- The problem
- Kobiton had shipped kobiton/automate, its plugin for Claude Code, and needed an outside review of where AI agents using it would go wrong: a skill that agents did not load, tool descriptions that did not match what the server returned, and gaps against the MCP specification.
- How we used Claude
- We did the review with Claude Code, Anthropic’s coding agent. We installed the plugin in Claude Code, ran its MCP tools against Kobiton’s real-device cloud, and used Claude Code to prepare every finding and pull request, which we checked before filing.
- In production
- kobiton/automate is Kobiton’s public plugin, installable today. The fixes listed on this page are merged into its main branch.
- Measured results
- 0 → 12 GitHub stars on kobiton/automate: 0 when our review began on 28 April 2026, 12 on 19 September 2026, counted on GitHub.
- 10 of 15 of our pull requests merged by Kobiton’s maintainers.
- 5 further fixes written by Kobiton’s own engineers, each citing the finding it closes.
- 2 → 8 of 8 skill frontmatter fields filled, and 12 of 12 MCP tools given retry-safety annotations.
- Kobiton’s goal
- “Our goal is to create a vibrant community which is focused around engineering and testers using our MCP with agentic processes via our automate repo.”
Stu Hume, VP Product Engineering, Kobiton
- In Kobiton’s words
- “I view you as a founding member of our team and MCP ecosystem / community, your contribution and value should be recognized.”
Stu Hume, VP Product Engineering, Kobiton
- Published
- By Intent Solutions on this page, and by Kobiton on its own blog in two articles by Jeremy Longshore (listed below).