NeuralDebug

AI-powered debugging for software (8 languages) and LLM/transformer reasoning. Debug programs with natural language via real debuggers (GDB, LLDB, CDB, JDB,...

This skill is internally consistent with a capable debugger/LLM tooling package, but it gives you a lot of power over your machine and models. Before installing or running it: - Review the upstream GitHub repository code (src/*) to confirm there are no unexpected network callbacks or telemetry. The SKILL.md directs you to clone and run repository code locally. - Treat it like native debugger/software: do not run it against sensitive production hosts or processes you don't trust. Attaching, reading memory, or writing memory can expose secrets. - Run installations and the server in an isolated environment (VM, container, or dedicated sandbox) because pip installs and model fine-tuning are resource-heavy and execute arbitrary Python code. - Be cautious with the 'exec_analysis' / inline-analysis features: they accept user-supplied code and the README's 'sandboxed' claim cannot be enforced by the skill metadata alone. - If you must use it interactively, restrict agent autonomy (do not allow unfettered autonomous invocation) and avoid pointing it at systems containing sensitive data. Verify saved fine-tuned models in ~/.cache/huggingface/hub/NeuralDebug-finetuned/ and remove them if undesired. If you want the skill but have limited trust, request a reproducible minimal build or pre-built package from a known maintainer, or run the tool only on throwaway environments.

Type: OpenClaw Skill Name: neuraldebug Version: 0.1.0 The NeuralDebug skill provides powerful system-level capabilities, including a 'Tool Forge' feature in 'llm-debugging.md' that allows for arbitrary Python code execution via the 'exec_analysis' command. While the documentation claims this is sandboxed, it represents a significant RCE risk. Furthermore, the skill provides broad access to the host system through multiple debugger backends (GDB, LLDB, JDB, etc.) across eight languages and requires cloning an external repository (https://github.com/DennySun2020/DeepRhapsody) for its core logic, which introduces supply chain concerns.