its_hub

Use when the user wants to run inference-time scaling on multiple prompts from a file (JSONL, CSV, or TXT). Applies to batch processing, evaluation runs, or dataset-level scaling.

Guides users through inference-time scaling with its_hub, including algorithm selection (Self-Consistency, Best-of-N, Beam Search, Particle Filtering), budget tuning, reward model setup, tool-calling integration, interpreting results, and troubleshooting. Use when the user is working with its_hub, asking about scaling algorithms, debugging scaling issues, or tuning inference quality.

Use when the user wants to set up inference-time scaling for the first time, or when its_hub is not yet installed/configured in the current environment.

Use when the user wants to run inference-time scaling on a prompt — detect environment, execute scaling, and present results. For algorithm selection, budget tuning, reward models, and troubleshooting, consult the inference-scaling-guide skill.