Bridging Tool Dependencies and Domain Knowledge: A Graph-Based Framework for In-Context Planning
This work addresses tool-augmented reasoning and planning, but appears incremental as it builds on existing graph and integration methods.
The paper tackles the problem of generating exemplar plans by modeling dependencies among tools and domain knowledge, resulting in improved plan generation through a unified graph-based framework.
We present a framework for uncovering and exploiting dependencies among tools and documents to enhance exemplar artifact generation. Our method begins by constructing a tool knowledge graph from tool schemas,including descriptions, arguments, and output payloads, using a DeepResearch-inspired analysis. In parallel, we derive a complementary knowledge graph from internal documents and SOPs, which is then fused with the tool graph. To generate exemplar plans, we adopt a deep-sparse integration strategy that aligns structural tool dependencies with procedural knowledge. Experiments demonstrate that this unified framework effectively models tool interactions and improves plan generation, underscoring the benefits of linking tool graphs with domain knowledge graphs for tool-augmented reasoning and planning.