AI
Hide your slop PR descriptions behind
Publication: Simon Willison's Weblog
Author: Not available in collected metadata
Source published: 09/11/2026, 04:25:05 UTC
Briefing created: 15/11/2026, 08:44:53 UTC
Based on a feed excerpt; full article content has not been acquired. Source evidence retrieved 10/11/2026, 00:12:24 UTC.
Briefings
A developer using AI coding assistants for pull requests discovered that AI-generated descriptions are accurate but lack human editorial value, causing immediate reader disengagement. To mitigate this, they implemented a GitHub Markdown feature called 'details summary' to hide the full AI-generated content and display only a high-level, human-curated hook. This approach allows developers to maintain the completeness of AI-assisted work while ensuring the initial summary reflects human judgment and effort.
Key points
- Developers using AI coding assistants for pull requests find that while AI-generated descriptions are accurate and comprehensive, they often feel like 'slop' due to excessive detail, leading to immediate reader disengagement.
- The developer implemented GitHub Markdown's 'details summary' feature to hide the full AI-generated content and display only a high-level, human-curated hook in the PR description.
Context
The article describes a personal workflow where developers use AI coding assistants to generate pull requests (PRs) for bundling commits and documenting solutions. The core finding is that AI-generated PR descriptions are too detailed for human readers, who prefer concise summaries. The solution involves using GitHub's 'details summary' feature to separate the full AI content from the brief human-curated introduction.
Limitations
The evidence is limited to a single developer's personal workflow and observations. It does not include quantitative data on user adoption rates, impact metrics, or broader industry statistics. The author's subjective assessment of whether the solution 'feels right' is not supported by external data.
Generated by Bittrees-hosted qwen35-2b sha256:aaf42c8b7c3c on 15/11/2026, 08:44:53 UTC. Based on publisher-provided feed evidence; may not cover the full original article. Check the source for details.
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