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Hiding AI-Generated PR Bloat with GitHub's <details> Tag

GitHub Pull Request LLM Developer Workflow Markdown Code Review
November 09, 2026
Source: Simon Willison

This summary and analysis were generated by AI from the original article at Simon Willison and may contain errors (how Viqus works). Read the source for full details.

Viqus Verdict Logo Viqus Verdict Logo 3
Workflow Polish, Not Tech Leap
Media Hype 4/10
Real Impact 3/10

Article Summary

The author notes that while coding agents excel at producing comprehensive, accurate PR descriptions, the sheer volume of detail makes them overwhelming for human reviewers. To combat this 'slop' effect, the author advocates using the native HTML <details><summary> tag within GitHub Markdown. This allows the core, human-curated summary to appear collapsed, while the full, agent-written technical details are hidden within the expandable section. This technique effectively filters the noise, presenting reviewers with a high-level hook and a clear indication of the work's scope without sacrificing technical depth.

Key Points

  • The <details><summary> tag in GitHub Markdown allows authors to present a concise, human-written summary while housing extensive, AI-generated technical details in an expandable section.
  • This method combats reviewer fatigue caused by overly verbose, comprehensive descriptions from coding agents.
  • The author recommends using a mnemonic, 'details-summary,' to remember the correct tag order for implementation.

Why It Matters

This is not a breakthrough in AI capability, but rather a crucial piece of developer tooling hygiene. It addresses the immediate, practical friction point of integrating advanced LLM outputs into established professional workflows like code review. By providing a standardized, low-friction mechanism for curating AI output, it improves the signal-to-noise ratio for highly technical audiences, which is a necessary maturation step for enterprise AI adoption.


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