Organizations: Univ. Lille, CNRS, Inria, UMR 9189 CRIStAL, Lille, France · Univ. Rennes, CNRS, Inria, IRISA, Rennes, France · Institut Universitaire de France (IUF), Paris, France
Engineering multi-agent systems (MAS) requires choosing agents, orchestration strategies, communication mechanisms, reasoning approaches, and memory configurations. These choices depend on framework-specific capabilities and abstractions, requiring developers to learn different APIs when exploring alternative implementations. We present GEAR, an open-source tool for configuring MAS and generating framework-specific implementations from a common specification. GEAR uses a feature-based representation to make configuration options and their constraints explicit, enabling users to validate specifications before code generation. Through connectors for ten agentic frameworks, users generate projects from the same specification and can then inspect reports describing framework-specific adaptations. A preliminary assessment of mapping feasibility identifies translation strategies for 271 of 320 evaluated feature-framework pairs (84.69%). GEAR supports developers prototyping agentic systems and researchers exploring MAS configurations across frameworks. GEAR is available as open-source software at https://github.com/brellsanwouo/gear-framework and a video demo is available at https://youtu.be/iwNi-oC2tCw.
Figures & tables
Fig. 1 : User workflow for the log-analysis demonstration in GEAR Studio: (1) configure LogParser and LogAnalyzer and connect them sequentially; (2) validate the specification; (3) generate projects for CrewAI and Google ADK.
Fig. 2 : Architecture and processing pipeline of GEAR .
Fig. 3 : Excerpt of GEAR ’s feature model.
Fig. 4 : Coverage of identified mappings between GEAR features and target frameworks (% of features mapped per framework).