Use cases · analyze
Analyze Code
Analyzing code is a core task for developers, security researchers, and engineers who need to understand, review, or audit codebases. AI agents excel at this by systematically examining source code, identifying patterns, detecting vulnerabilities, and extracting ownership information. They can process large codebases quickly, apply static analysis techniques, and generate structured reports. Below are 9 skills we evaluated for this task.
9 skills for this task
security-threat-model
Repository-grounded threat modeling that enumerates trust boundaries, assets, attacker capabilities, abuse paths, and mitigations, and writes a concise Markdown threat model.
security-ownership-map
Analyze git repositories to build a security ownership topology (people-to-file), compute bus factor and sensitive-code ownership, and export CSV/JSON for graph databases and visualization.
ctf-rev
Solve CTF reverse engineering challenges using systematic analysis to find flags, keys, or passwords.
mlx
Use when working with Apple's MLX or MLX-LM: fact-checking current behavior against upstream source/runtime, patching MLX-based repos, porting PyTorch/JAX code to MLX, validating lazy evaluation,…
solodit
Search 50,000+ smart contract vulnerabilities from Cyfrin Solodit. 8 MCP tools with intelligent caching for searching, filtering, and analyzing blockchain security findings.
kernel-dev-skill
Linux kernel development skill grounded in local references/labs and references/lectures materials.
author-contributions
Identify all files a specific author contributed to on a branch vs its upstream, tracing code through renames.
dig
Investigation-only mode for understanding bugs, features, or system behavior without making changes.
eval-harness
Formal evaluation framework for Claude Code sessions implementing eval-driven development (EDD) principles
Common questions
- How can an AI agent help analyze code for security vulnerabilities?
- An AI agent can perform threat modeling and identify potential security issues by scanning code for common patterns, misconfigurations, and known vulnerability signatures. It can generate a structured threat model report, mapping out attack surfaces and suggesting mitigations.
- Can an AI agent reverse engineer compiled code?
- Yes, specialized skills like CTF reversing enable an AI agent to decompile and analyze binary executables, extract logic, and understand algorithms. This is useful for malware analysis, legacy code understanding, or competitive reverse engineering challenges.
- What kind of code analysis can an AI agent perform for kernel development?
- For kernel development, AI agents can analyze driver code, check for concurrency issues, validate memory management, and ensure compliance with kernel coding standards. They can also generate ownership maps to understand code responsibilities and dependencies.