mlsanityData to 7 Oct 2026

SkillGraph: Graph Foundation Priors for LLM Agent Tool Sequence Recommendation

arXiv 2604.19793 ↗First posted 7 Apr 2026cs.AI cs.CL cs.IRcited by 0

On the map: LLM agents and tool use → Tool learning and function calling

Abstract (arXiv)

LLM agents must select tools from large API libraries and order them correctly. Existing methods use semantic similarity for both retrieval and ordering, but ordering depends on inter-tool data dependencies that are absent from tool descriptions. As a result, semantic-only methods can produce negative Kendall-τ in structured workflow domains. We introduce SkillGraph, a directed weighted execution-transition graph mined from 49,831 successful LLM agent trajectories, which encodes workflow-precedence regularities as a reusable graph foundation prior. Building on this graph foundation prior, we propose a two-stage decoupled framework: GS-Hybrid retrieval for candidate selection and a learned pairwise reranker for ordering. On ToolBench (9,965 test instances; ~16,000 tools), the method reaches Set-F1 = 0.271 and Kendall-τ = 0.096; on API-Bank, Kendall-τ improves from -0.433 to +0.613. Under identical Stage-1 inputs, the learned reranker also outperforms LLaMA-3.1-8B Stage-2 rerankers.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Tool learning and function calling, one of 16 directions in LLM agents and tool use. Builds on 11 of its 22 references that are in the map. First posted on arXiv 7 Apr 2026.

Builds on

11 of 22 references.

Closest ancestors · 4

Same direction, newest first

  1. 2023ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs31 Jul
  2. 2023Tool Learning with Foundation Models17 Apr
  3. 2023API-Bank: A Comprehensive Benchmark for Tool-Augmented LLMs14 Apr
  4. 2023Toolformer: Language Models Can Teach Themselves to Use Tools9 Feb

Other references · 7

  1. 2024The Llama 3 Herd of Modelscited by 14,192
  2. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,160
  3. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,049
  4. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,355
  5. 2020Dense Passage Retrieval for Open-Domain Question Answeringcited by 3,779
  6. 2018Self-Attentive Sequential Recommendationcited by 1,169
  7. 2021Dynamic Graph Neural Networks for Sequential Recommendationcited by 57

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  1. 2026Tools Are Not Islands: Set-Level Tool Retrieval for LLM Agents via Query-Conditioned Hyperedge Prediction
  2. 2026Toollery: Scaling LLM Agents to Thousands of Skills and Tools
  3. 2025GRETEL: A Goal-driven Retrieval and Execution-based Trial Framework for LLM Tool Selection Enhancing
  4. 2026Complete Cyclic Subtask Graphs for Tool-Using LLM Agents: Flexibility, Cost, and Bottlenecks in Long-Horizon Workflows
  5. 2026FlowScout: From Execution Feedback to Reliable Tool-Using Agent Workflows
  6. 2026SkillDAG: Self-Evolving Typed Skill Graphs for LLM Skill Selection at Scale
  7. 2026Graph-of-Skills: Dependency-Aware Structural Retrieval for Massive Agent Skills
  8. 2026SING: Synthetic Intention Graph for Scalable Active Tool Discovery in LLM Agents