Simon Willison released datasette-mcp 0.2, changing MCP SQL results to object arrays for better small-model usability.
Datasette-mcp 0.2 changes the execute_sql 'rows' output from an array of arrays to an array of objects, helping weaker models avoid losing track of positional column mappings. The plugin now depends on mcp>=2.1.1. This is the first non-alpha release, and the author reports using it extensively.
Signed Rescue Routing improves LLM cascade efficiency by predicting when a larger model actually corrects a smaller one rather than uncertainty.
Signed Rescue Routing (SRR) is a budgeted cascade method that separately predicts rescues and regressions when escalating from a small to a large model, ranking requests by their signed difference. The authors prove this signed conditional gain is Bayes-optimal under a fixed escalation budget and add only a lightweight two-head router needing small-model output statistics at deployment. Evaluation with Qwen3-4B and Qwen3-8B on MMLU, HellaSwag, and ARC-Challenge shows better accuracy-compute tradeoffs than entropy routing and learned error predictors.