Simon Willison released commit-rewriter 0.1, a web app that lets users edit commit messages for a repository. The tool is useful for cleaning up commits that contain internal references or unwanted code before publication. After editing, it creates a timestamped branch to preserve the original state and rewrites the selected commits.
The article announces the release of commit-rewriter version 0.2. It adds support for operating on branches other than the default, allowing users to run the tool against a specified branch with the command `uvx commit-rewriter --branch other`. The update is tagged under git.
arXiv:2508. 12232v5 Announce Type: replace-cross Abstract: Issue-to-commit link recovery in software repositories is fundamental to software traceability and project management, yet it remains a challenging task.
GitHub Models is now retired I missed this news until today, when the GitHub Actions run for my simonw/research repository failed with this error message: GitHub Models is temporarily unavailable as part of a scheduled retirement brownout. That message is already stale, because the retirement has been completed.
Release: llm 0.37.1 A bugfix release for LLM, with contributions from Steven Huang, Tao An, Arjan Mossel, and XQ. Tags: llm
The article recounts a challenging debug session that was significantly aided by an AI assistant. Despite the AI initially claiming the problem was unsolvable and suggesting a report be written instead, it persisted, adding debug code and analyzing it as the author pushed forward. Ultimately, the author credits the AI with writing the commit message for the fix.
arXiv:2607. 13111v1 Announce Type: cross Abstract: Distinguishing semantic-preserving commits from changing ones remains an open challenge in software repository mining.
ComBeautify is a tool that automatically generates Conventional Commits Specification (CCS)-compliant commit messages by combining context-preserving summarization of Git diffs with large language models. It learns commit categories from historical data rather than relying on manually curated definitions, and also produces the CCS description component. Evaluation on 13 languages, 6,500 repositories, and over 20 million commits shows that project-specific training can outperform generic baselines by up to three times, with summarization accuracy reaching 95.25% on a manually curated dataset.
The article describes a developer’s strategy for ensuring that an agent uses a diagnostics library by implementing a pre‑commit hook that scans the git diff for direct calls to observability modules. If such calls are detected, the commit fails and a prompt is injected, instructing the agent to use the diagnostics library instead. This approach eliminates the need for manual code updates and maintains consistency across the codebase.
The release of llm 0.36 introduces new OpenAI models gpt-6-sol and gpt-6-luna, and adds support for model plugins to declare that they do not support conversations via supports_conversation = False. When such models receive assistant or tool history, llm raises a ConversationNotSupported error and the chat interface rejects them before starting a session. Additional changes include wrapping reasoning traces in Markdown output with <details> tags and bug fixes from five contributors.
The paper investigates how large language models (LLMs) can propose changes to Kubernetes configuration files in a GitOps workflow. It shows that having the model directly generate edited files or diffs is unsafe for unattended automation, as current text‑generation strategies either fail to apply patches or silently misapply them. The authors propose a deterministic, minimal‑diff approach where the model emits only a structured intent for a field change, and a pipeline locates and replaces the exact character span in the raw YAML, preserving formatting and comments while guaranteeing correctness and O(1) generation cost.
Release: sqlite-utils 4. 2 Lots of improvements in this one relating to the table.
The paper introduces “Revise”, a runtime system that performs validity-guided, fine-grained recovery for online revisions in structured agent workflows. When a revision arrives, Revise intersects the change with recorded data and control dependencies, propagates the impact through the partially executed DAG, stops invalid work, preserves unaffected progress, and recomputes only the affected region. Experiments on real coding‑agent traces and LangGraph/LLMCompiler applications show that Revise matches a latest‑version oracle, reduces model calls by up to 56%, and improves service‑level objective goodput under load.