HealthClaw能记住你的健康习惯和变化，测试中准确率从0.2%飙到45.7%，还更保护隐私，开源可用。
HealthClaw是一个开源智能体架构，专为长期个人健康管理设计。它分离共享安全规则和医疗知识与私有纵向记忆（包含档案事实、可复用程序和情景痕迹）。在包含900个纵向支持探测的合成一年基准测试中，HealthClaw将答案准确率从当前查询提示的0.2%提升至45.7%，同时提示侧上下文暴露量比全历史提示降低71.7%。在100个隐私探测中，HealthClaw产生了更高的隐私感知答案质量且更少不安全披露。在九项200例生物医学任务中，任务特定主要指标平均绝对增益为27.0个百分点，其中七项经过错误发现率校正后仍显著。
A Self-Evolving Agent for Longitudinal Personal Health Management
Personal health management unfolds over repeated encounters, yet most health AI systems treat each request in isolation. We developed HealthClaw, an open-source agent architecture that updates support as a person's routines, preferences, measurements and risks change. It separates shared safety rules and medical knowledge from private longitudinal memory containing profile facts, reusable procedures and episodic traces. After each episode, induction determines what should update the profile, revise a procedure, remain episodic or be excluded. We evaluated HealthClaw with a synthetic year-long benchmark and nine 200-case biomedical tasks. Across 900 longitudinal support probes, answer accuracy increased from 0.2% with current-query prompting to 45.7% with HealthClaw, while prompt-side context exposure was 71.7% lower than with full-history prompting. In 100 privacy probes, HealthClaw produced higher privacy-aware answer quality and fewer unsafe disclosures than both baselines. Across the biomedical tasks, the mean absolute gain in the task-specific primary metric was 27.0 percentage points, and seven gains remained significant after false-discovery-rate correction. These offline benchmarks support governed, self-evolving memory for longitudinal personal health agents, although clinical effectiveness requires prospective evaluation. HealthClaw is publicly available at https://github.com/HC-Guo/HealthClaw.