Interviewers Ask About Claude Code Skills—What If You Haven’t Used /simplify?

When I finally tried Claude Code’s /simplify command, I realized none of my peers who also use Claude Code knew about it. The command reviews the code you just wrote (or a specified file), finds hidden problems, and automatically fixes them.

What /simplify Is

Claude Code commands that start with / come from two sources: hard‑coded commands such as /clear, /compact, and bundled skills like /simplify, /batch, /review, /debug. Bundled skills are prompt‑based: when invoked, Claude loads a specific Markdown playbook and runs sub‑agents to perform multi‑step workflows.

History

In January 2026 the Anthropic team open‑sourced a plugin called code‑simplifier (repo anthropics/claude-plugins-official). It focused on single‑file refactoring. In February 2026 Claude Code v2.1.63 integrated this plugin as the built‑in bundled skill /simplify, adding three parallel agents, multi‑file project‑level context, and zero‑configuration usage.

How to Use

You can run /simplify without arguments to let it diff the current Git changes, or specify a focus direction, for example:

/simplify thread safety
/simplify SQL performance
/simplify exception swallowing

You can also target a specific class or module, e.g. /simplify MarketDataService.

Review Mechanism

The command works in three steps:

Determine the review scope. Without parameters it runs git diff on uncommitted changes; if the working tree is clean it reviews the latest commit. Providing a class name makes it load the whole file for full‑file analysis.

Launch three agents in parallel. Each agent examines the same diff from a different perspective.

Aggregate and fix. The agents report findings, Claude decides which are true issues versus false positives, and then applies the fixes automatically.

Three Agents

Code Reuse Agent : Detects duplicated logic, e.g., a custom requireNonBlank() that already exists as InputValidator.requireNonBlank().

Code Quality Agent : Flags design problems such as hard‑coded duplicate strings, near‑identical methods, or classes that mix unrelated responsibilities.

Efficiency Agent : Looks for performance issues like creating objects inside loops, unnecessary use of ConcurrentHashMap in single‑threaded contexts, or missing caches.

Real‑World Example 1: Pre‑PR Self‑Review

After a large refactor (26 files, 443 new lines) I ran /simplify. It reported six real problems, the most critical being a Spring transaction failure. The code snippet:

public void initializeDefaultWatchlist(Long userId) {
    // Redis distributed lock + double‑check
    doInitializeDefaultWatchlist(userId);
}

@Transactional(rollbackFor = Exception.class)
protected void doInitializeDefaultWatchlist(Long userId) {
    groupService.save(defaultGroup);
    stockService.saveBatch(initialStocks);
}

Because the method is called internally ( this.doInitializeDefaultWatchlist()), Spring AOP proxies are bypassed and @Transactional never takes effect. When saveBatch throws, the earlier groupService.save is not rolled back, leaving an empty group in the database.

The agents flagged the self‑call and the ineffective transaction as high severity. /simplify suggested switching to programmatic transactions using TransactionTemplate:

@RequiredArgsConstructor
public class WatchlistService {
    private final TransactionTemplate transactionTemplate;

    private void doInitializeDefaultWatchlist(Long userId) {
        transactionTemplate.executeWithoutResult(status -> {
            groupService.save(defaultGroup);
            stockService.saveBatch(initialStocks);
        });
    }
}

The fix uses PlatformTransactionManager directly, making the transaction work regardless of proxying.

Result: 5 files changed, 38 lines removed, six issues fixed, and the project compiled cleanly.

Real‑World Example 2: Module‑Level Review of MarketDataService

Running /simplify MarketDataService (≈570 lines) uncovered eight issues, two of them high severity:

Bug in period mapping: The normalizePeriod switch incorrectly maps "year" to "month".

case "year", "yearly", "y" -> "month"; // Bug! should be "year"

Redundant local circuit breaker: The class maintains its own dataSourceStates breaker while also injecting DataSourceHealthService that performs the same function with a different cooldown, causing inconsistent state.

Fixes applied:

Corrected the mapping to year → "year" (1 line).

Removed the entire local breaker implementation ( dataSourceStates, related inner class, methods, constants, and imports).

Pre‑compiled five regular expressions in normalizeStockCode as static final Pattern.

Five additional medium/low issues (copy‑paste in fetch, redundant calls in enrichValuation, etc.) were recorded for future architectural improvement.

Suitable Scenarios

Pre‑PR self‑review: Low‑cost, high‑value scan of multi‑file changes before submission.

Post‑refactor quality check: Verify that a large code cleanup did not introduce new design flaws.

Code‑review assistant: Surface problems that require domain knowledge, such as Spring proxy behavior or MyBatis batch semantics.

Unsuitable Scenarios

Full‑project audit: /simplify only works on diffs or a single file; it cannot scan every file in a large repository at once.

Style formatting: It does not enforce brace placement, indentation, or whitespace—tasks for formatters or linters.

Security audit: While it may spot obvious regex‑based data‑leakage, comprehensive SAST tools are required for security reviews.

Core Difference from Traditional Tools

Rule‑based tools like SonarQube or Checkstyle can detect patterns (e.g., methods longer than 80 lines) but cannot understand framework semantics. /simplify knows how Spring proxies work, distinguishes TransactionTemplate from @Transactional, and is aware of project dependencies such as Caffeine.

Practical Tips

Keep commit size reasonable (10‑20 files) so agents can locate issues efficiently.

Run /simplify immediately after a refactor while the context is fresh.

Prioritize high‑severity findings; medium/low can be ignored if they have negligible impact.

Validate false positives—agents may flag harmless code (e.g., an unnecessary ConcurrentHashMap bean).

Integration with MiniMax/GLM

If you cannot install Claude Code locally, you can use MiniMax or GLM as the underlying model via the OpenAI‑compatible API. Install Claude Code with: npm install -g @anthropic-ai/claude-code Obtain API keys from the MiniMax or GLM portals, then use the CC Switch tool (GitHub: https://github.com/farion1231/cc-switch) to switch providers and configure the keys.

After configuration, run claude in any project directory, trust the folder, and the /simplify command becomes available.

Conclusion

/simplify

excels at finding bugs that require deep framework knowledge, such as Spring transaction pitfalls or subtle logic errors, while remaining lightweight and zero‑config. It complements, rather than replaces, traditional linters and security scanners.