An arXiv paper submitted on 20 October 2026 by Rui Gong and 11 co-authors presents S-Agent 2.0, a spatial reasoning agent that equips an off-the-shelf general coding agent with a command-line perception toolkit and a persistent scene memory, so the model acquires scene evidence, remembers it and interprets readings in plain spatial language. The authors report the toolkit lifts Qwen3.8-27B by 13.9 points on MMSI-Bench and 20.5 points on ReVSI over the same agent without tools, and Gemini-3.8-Flash by 11.2 and 9.6 points; with the open backbone S-Agent 2.0 scores 66.5 and 82.3, ahead of SpatialClaw on the same backbone (62.6 and 74.5), and with Gemini-3.8-Flash it reaches 74.1 and 90.5 against 67.0 and 79.7. The paper says the system also works across different coding-agent harnesses such as Codex and Claude Code, and that tool gains shrink as the backbone becomes more capable, though the authors say their gain on ReVSI holds at 9.6 points while SpatialClaw's falls from 13.2 to 2.7.