Code Review Request

Coding

Set the review focus and conventions, and get issues ranked by severity with a reason and a fix for each.

Fill the blanks and it copies as you filled it

Review this code: 

- Review focus: 
- Team conventions: 
- Output:  issues ranked by severity, each with a one-line reason + a fix example

0 of 4 blanks filled · anything left blank copies with its brackets

Compared with asking the same thing without the length and format lines.estimate

Estimated output tokens

700

Asked loosely

180

This prompt

Energy (Wh)

1.215

Asked loosely

0.423

This prompt

Tokens estimated from characters; energy measured by Jegham et al. 2025.

What that saves

15.8 Wh · 5.54 gCO₂e · 74 mL — assuming 20 uses a day — the global average is 3.7 (Chatterji et al. 2025)

Tap a card for how the conversion was done.

Reported backfire — Specifying output lengthSpecifying a length longer than needed backfires (a 34% increase in 11% of scenarios)

Reported backfire — Specifying output formatA 78% increase in one GPT-4o scenario. The paper classifies this one as apply-selectively

Where these figures come from

Published figures for the rule itself — not what this prompt saves.

Specifying output length

38.7%mean reduction · 95% CI 29.7–47.7%

Podder et al. 2026 BP#5 · 18 use cases / 57 prompts

by modelGPT-4o 35%Command R+ 49%Mistral-7B 32%

Reduced in every scenario. No backfire reported

Specifying output format

49%mean reduction · 95% CI 37–61%

Podder et al. 2026 BP#6 · 14 use cases / 45 prompts

by modelGPT-4o 40%Command R+ 50%Mistral-7B 57%