Aug 2026· 2 citations· ⚡ 1 influential· 44 references
Computer Science
TL;DR
This work introduces Agentic Commerce World (ACWorld), an environment for evaluating such agents across ongoing transactions, and validates agent actions before updating shared transaction state and records the resulting interactions, making agent behavior auditable and evaluation reproducible.
Abstract
In vibe coding, people describe software in natural language and delegate implementation to AI agents. By analogy, vibe commerce allows people to express buying or selling goals in natural language and delegate the corresponding tasks to agents. Commerce, however, requires independently controlled Buyer and Merchant agents to interact in a shared market while preserving their private objectives and distinct authority. We introduce Agentic Commerce World (ACWorld), an environment for evaluating such agents across ongoing transactions. Through its Vibe Commerce Protocol (VCP), ACWorld validates agent actions before updating shared transaction state and records the resulting interactions, making agent behavior auditable and evaluation reproducible. The ACWorld Benchmark contains a 200-task capability-coverage track and a 60-task large-catalog track that searches 785,022 transactable listings. Across ten models, mean scores range from 65.9% to 85.6% and from 56.1% to 91.4%, respectively. Our analysis shows that process-level evidence is necessary: final state alone can miss evaluated errors, incomplete trajectories still retain useful process signals, and large-catalog tasks expose bottlenecks across stages.
Enterprise AI agents now read tickets, documents, and web pages and then act on what they find through tool protocols such as the Model Context Protocol (MCP). Because an agent combines untrusted input with delegated privileges, it creates a path from attacker-influenced content to privileged action that earlier Zero T...
A. Solanke· World Journal of Advanced En...· 0 citations
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This paper proposes the Evaluation Context Protocol (ECP), an early-stage, vendor-neutral framework intended to act as a portable evaluation contract layer for agentic systems and describes an open-source reference implementation that includes adapters for LangChain, LlamaIndex, CrewAI, and PydanticAI.
A policy algebra is proposed that defines the reliability envelope within which agent capability may be exercised and provides researchers and practitioners with formal correctness conditions, executable decision semantics, and trace evidence for building agents that are not only capable, but reliably capable.
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This work formalizes four representative agent payment protocols: x402, MPP, ACP, and AP2 in Tamarin, and constructs source-grounded models that capture each protocol's roles, state, trust assumptions, and lifecycle transitions.
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Experiments on guideline-following and artifact-generation tasks show that specifications can serve not merely as behavioral guidance, but as authority over compliant execution and completion.
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