It's analogous to how in the early days you could see benefits by telling the models to "think step by step". /code-review is something like "review angle by angle". "Consider removed behavior" and also "Look at language gotchas" and also "Look at test changes"...etc. Yes these are all somewhat implicitly already part of what "code review" means, but the models perform best with explicitness.
If you want my 2c as a power user: just don't think about it and use /code-review xhigh --fix. This will cover like 98% of what you want out of code review. It's a good skill.
Outsourcing comprehension to a machine is probably gonna cost you more time in the long run.
- Defining the issue/ticket, what "success" looks like (if I have a good idea of this), high level approach guidance 50%
- Dispatch agent to work on it 5%
- Occasionally return and nudge agent + send /simplify or /code-review 5%
- Look at the code/session summary, divergences from the plan, ask followup questions 40%
Occasionally yes there is some solution the AI chose that is suboptimal and I would prefer fixed in a different way. Mostly though it's straightforward.
Is there something equivalent when coding in the first place? Eg /code high “prompt”
https://github.com/anthropics/claude-code/blob/main/plugins/...
This stuff all seems so nebulous to me and I’ve yet to see anything that says use x in y situation. So I default to higher effort levels than I likely need.