Claude Code Review: A 2026 Terminal Checklist
Claude Code diffs deserve a deliberate review pass
My 2026 rule for reviewing changes written by Claude Code is simple: review the evidence, not the explanation. A convincing summary can hide a missing authorization check, an unnecessary dependency, or a test that merely repeats the implementation. The useful question is not whether the code looks human. It is whether I can explain its behavior, failure modes, and rollback path before merging.
I separate generation from acceptance. Claude Code can propose patches and run checks, but the acceptance criteria come from the issue, existing contracts, and repository conventions. Here is the checklist I keep beside the terminal.
Start with the actual Git diff and task boundary
Before reading the agent's recap, run git status --short, git diff --stat, and git diff. For committed changes, inspect the branch diff against its merge base. Look for new files, deleted assertions, lockfile churn, and formatting noise that can bury meaningful behavior.
- Confirm every changed file supports an explicit acceptance criterion.
- Separate unrelated refactors before evaluating the requested behavior change.
- Inspect repository instructions, build scripts, and CI configuration changes carefully.
- Check that generated files match their sources and regeneration commands.
If the patch feels too large to reason about, ask for smaller commits. A tidy summary does not make a sprawling diff reviewable.
Trace Claude Code changes across trust boundaries
Follow one request from its entry point through validation, authorization, persistence, and response serialization. Then trace the failure path. Agent-written code often looks locally correct while assuming another layer handles ownership checks, retries, or transaction boundaries.
- Verify authorization against the requested resource, not just authentication.
- Check untrusted input before shell execution, database access, or outbound requests.
- Inspect logs and errors for secrets, tokens, and sensitive payloads.
- Review timeouts, cancellation, retries, and duplicate side effects together.
For payment callbacks or job handlers, explicitly test replay behavior. For multi-tenant APIs, request another tenant's resource. Those probes tell me more than another pass over happy-path naming.
Make tests challenge the patch instead of endorsing it
Ask Claude Code which existing test would have failed before the fix. Then verify that claim yourself. A newly added test is stronger evidence when it fails against the original implementation and passes with the patch. Do that comparison in an isolated worktree rather than disturbing uncommitted work.
- Run the targeted tests yourself and record the exact commands.
- Add boundary cases that were absent from the implementation prompt.
- Check whether mocks bypass the behavior the test claims to verify.
- Run relevant lint, type, integration, and build checks before approval.
Treat unavailable infrastructure as an explicit verification gap. Do not translate “could not run” into “probably passes.”
Inspect dependencies, migrations, and operational costs
Every new package creates maintenance work. Confirm that its APIs exist in the pinned version, examine its install scripts, and check whether an existing dependency already solves the problem. For schema changes, review locking, backfill duration, mixed-version compatibility, and recovery if deployment stops halfway.
Also inspect expensive loops, unbounded queries, and new model calls. In AI-backed features, record token usage, cache behavior, timeout budgets, and retry limits. A correct result can still be an operational regression.
Use a second model as a reviewer, not an authority
A separate review pass can surface blind spots. For example, ask GPT-6 Astra to challenge a Claude Sonnet 5.5 patch using the acceptance criteria and diff. Require file references and concrete failure scenarios; reject findings that cannot be reproduced or justified.
Fluxo keeps that workflow in the editor and terminal: one key and one base URL, https://api.fluxorelay.com, for Claude, GPT, Gemini, DeepSeek, Kimi, GLM, Qwen, Grok, and more. It works with Claude Code, Codex, Gemini CLI, and any OpenAI SDK. Billing follows real tokens, including cache reads and writes, with no monthly fee.
Record merge evidence before closing the review
Leave the commands run, remaining risks, and rollback plan in the pull request. Keep referral incentives separate from technical recommendations: Fluxo users earn a referral share when invited people pay, but review evidence should stand independently. If this workflow fits your setup, consider creating a Fluxo account.