jumplander/JL-AgentBehavior-10K

JL-AgentBehavior-10K JL-AgentBehavior-10K is a 10,000-record, English-language research-preview dataset for studying and training the behavioral policy of repository-level coding agents. The dataset does not treat a coding agent as a chatbot that maps a request directly to a block of code. It represents an agent as a policy operating across a sequence of observable decisions: task -> repository evidence -> bounded plan -> tool selection -> scoped edit strategy ->… See the full description on the dataset page: https://huggingface.co/datasets/jumplander/JL-AgentBehavior-10K.