The study ran the same 80 tasks under claude-agent-sdk and deepagents on claude-opus-4-8, and under openai-codex SDK and deepagents on gpt-5.5. Neither contrast resolved an average advantage: -1.25 pp for Opus 4.8 and +1.25 pp for GPT-5.5. The Opus average combines opposite strata: the native harness trails by 9.0 pp on the 61 repository tasks and leads by 23.7 pp on the 19 contest tasks, a partition chosen after seeing the data and needing a designed replication. Also, 22 of 81 runs cancelled at the wall-clock ceiling had produced a passing patch. Re-priced from raw per-turn usage at frozen list prices, the neutral harness cost 1.3 to 1.6 times as much per solved task on Opus 4.8 and 1.2 times on GPT-5.5, though billed ordering is unresolved because 58 Anthropic runs left no usage record.
Useful Automation/Report
MCP Changes Integration from Fixed Endpoints to Dynamic Tool Discovery
n8n has published a guide comparing the Model Context Protocol (MCP) with traditional APIs, explaining when to use each and how to combine them…
