From coding
Review code for potential issues and improvements. Use when asked to review specific files, functions, or code sections.
How this skill is triggered — by the user, by Claude, or both
Slash command
/coding:reviewThis skill is limited to the following tools:
The summary Claude sees in its skill listing — used to decide when to auto-load this skill
Review the mentioned code for potential issues and improvements.
Review the mentioned code for potential issues and improvements.
Review critically — don't assume correctness. Question every design choice and flag anything that would fail a production code review. Assume any prior git state or file contents you gathered is stale, especially if the user re-runs this skill or asks you to re-read.
Study the project's coding standards and design principles — e.g. CLAUDE.md, AGENTS.md, or design docs in the repo, if present.
Only report verified bugs — things that are actually wrong. Do NOT report:
For EVERY potential issue, you MUST complete these steps before reporting:
Use subagents liberally:
If you find zero real issues after thorough research, say "No issues found." Do not pad the list.
Correctness
Code quality
Testing gaps
Step 1 — write up every issue as text first. For each issue use a short ID (e.g. #A, #B) and include:
Step 2 — only after all issue blocks are written, use AskUserQuestion so the user can accept, veto, or comment on each one. The question text is just the ID (e.g. Accept #A?) — it is NOT a substitute for the write-up above. Never jump straight to AskUserQuestion without the text write-up; the user can't evaluate #A if they've never seen what #A is.
Edit, Write, and Bash are available so that, once the user accepts a finding, Claude can apply the fix and run tests to prove the bug and validate the fix in the same session. The proof-before-reporting discipline is what keeps this from turning into drive-by "improvements."
CLAUDE.md, docs/DESIGN-PRINCIPLES.md, etc.).npx claudepluginhub photostructure/claude-code-skills --plugin codingGuides creation, editing, and verification of skills for AI coding agents using test-driven development with subagent scenarios. Use when authoring or debugging skills.