Use cases · debug
Debug Code
Debugging code is the process of identifying, isolating, and fixing errors or unexpected behavior in software. AI agents excel at this task by systematically analyzing code, reproducing issues, and suggesting targeted fixes. They can inspect logs, trace execution paths, and reason about root causes faster than manual debugging. Below are 3 skills we evaluated for this task.
3 skills for this task
claude-api
Reference for the Claude API / Anthropic SDK — model ids, pricing, params, streaming, tool use, MCP, agents, caching, token counting, model migration.
kernel-dev-skill
Linux kernel development skill grounded in local references/labs and references/lectures materials.
luamake
Luamake 构建系统指南——用于当前项目的 `luamake` / `make.lua` / Ninja 生成流程。当用户需要编写、修改、排查或理解 `make.lua`、目标定义、`lm:conf`、`deps` / `objdeps`、代码生成、Lua C 模块、Bee 运行时集成，或需要解决当前项目中由 `luamake` 驱动的构建问题时，使用此 skill。即使用户没有明确提到…
Common questions
- How can an AI agent help debug my code?
- An AI agent can analyze your codebase, reproduce bugs, and suggest fixes by reasoning through the logic. It can also inspect error logs and trace execution to pinpoint root causes.
- What types of bugs can AI agents debug?
- AI agents can handle syntax errors, runtime exceptions, logic errors, and performance issues. They are particularly effective for common patterns and reproducible bugs.
- Do I need to provide my entire codebase for debugging?
- No, you can provide specific files, error messages, or a minimal reproducible example. The more context you give, the more accurate the debugging suggestions will be.