社区宜居性通常依赖静态建成环境指标进行评估，例如设施邻近性、街道连通性及公共空间可达性。此类指标描述了可获得的机会，但并未直接反映具有不同移动能力、家庭角色、日程安排及照护责任的居民对社区的实际体验。本文提出一种原型框架，结合空间知识图谱（KG）与大型语言模型（LLM），生成并修订家庭日程表，继而开展基于规则的可行性检验与基于GIS的网络具象化。该空间KG整合了居民、住宅、设施、社区背景及采样道路枢纽；Graph-RAG为每个家庭检索其周边空间上下文，包括候选兴趣点（POI）及估算步行时间，以支持日程规划型LLM。LLM生成结构化的家庭日程表，规则则用于轻量级修正及可审计的可行性检验；随后LLM根据识别出的可行性问题对日程表进行修订。路径规划模块基于路网推导实际出行路径、出行时间、交通方式及事件历史。所生成的事件支持针对合成居民智能体的访谈，内容涵盖日常便利性、出行负担、活动可行性及家庭协作。在深圳某社区的原型演示表明：设施名义上的可用性并不必然意味着便捷可达；移动能力受限的居民及承担照护责任的家庭面临更高的出行与协调负担。该框架提供了一种可审计的方法，将空间机会、家庭活动约束与居民个体化的宜居性理解相联结，同时确保模拟体验与真实体验保持区分。

Neighborhood livability is commonly assessed with static built-environment indicators, such as facility proximity, street connectivity, and access to public space. These measures describe available opportunities but do not directly represent how residents with different mobility capacities, household roles, schedules, and care responsibilities experience the neighborhood. This paper presents a prototype framework that uses a spatial knowledge graph (KG) and large language models (LLMs) to generate and revise household schedules, followed by rule-based feasibility checking and GIS-based network materialization. The spatial KG integrates residents, residences, facilities, neighborhood context, and sampled road hubs; Graph-RAG retrieves each household's nearby spatial context, including candidate POIs and approximate walking times, for the scheduling LLM. The LLM produces structured household schedules, while rules are used for lightweight repairs and auditable feasibility checks. The LLM then revises schedules in response to identified feasibility issues. A routing module derives the actual travel paths, travel times, modes, and event histories from the road network. The resulting events support synthetic resident-agent interviews about daily convenience, travel burden, activity feasibility, and household coordination. A prototype demonstration in a Shenzhen neighborhood shows that nominal facility availability does not necessarily imply convenient access: residents with limited mobility and households with care responsibilities experience greater travel and coordination burdens. The framework offers an auditable way to connect spatial opportunity, household activity constraints, and resident-specific livability interpretation, while keeping simulated experience distinct from observed perception.