JetbrainsOleg ZinovyevAnnouncement
Stop Guessing at Hard Faults
Summary
CLion 2026.2.2 adds an AI skill for diagnosing ARM Cortex-M hard faults through dedicated MCP tooling. Embedded debugging typically requires decoding CFSR and HFSR, matching the faulting program counter to disassembly, and reproducing crashes because default handlers often report only that a fault occurred. When triggered by a stopped hard-fault-family handler or relevant fault evidence, the skill provides decoded status registers, the hardware-stacked exception frame, SVD-decoded peripheral registers, disassembly, and nearby memory to an agent. It supports any debugging tool, including Lauterbach TRACE32, Segger J-Link, and ST-LINK, and can produce a bug location and fix, with optional rerunning to verify the program. The skill is enabled by default but requires CLion’s MCP server; it works in AI chat and CLI mode for Claude Code and Codex, while GitHub Copilot supports CLI mode only.
Context
Embedded hard-fault investigation requires manual decoding of fault registers, correlating the faulting program counter with disassembly, and sometimes reproducing crashes. Default handlers commonly halt execution without explaining why the fault occurred.
Approach / What changed
The clion-embedded-hardfault skill uses CLion’s MCP tooling to provide decoded fault status registers, the hardware-stacked exception frame, SVD-decoded peripheral registers, disassembly, and memory around the faulting instruction to an agent.
Takeaways
The skill activates when a session stops in HardFault_Handler, MemManage_Handler, BusFault_Handler, or UsageFault_Handler, or when relevant fault-register or exception-frame terms are mentioned.
The tooling is vendor-agnostic and supports Lauterbach TRACE32, Segger J-Link, ST-LINK, and other debugging tools.
The skill is available in AI chat and CLI mode for Claude Code and Codex, but only in CLI mode for GitHub Copilot.
Source and freshness
- Source
- blog.jetbrains.com
- Published
- Added to Yomu
- Last updated
Summaries are generated from the original by a language model. Check the original before relying on it.
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