@aa2246740/pi-fusion

This Skill addresses the issue of unreliable answers from a single large model by enabling cross-validation across multiple models. In practice, developers often need to compare outputs from different models, manually merge results, and determine the optimal answer—a tedious process lacking standardized evaluation. Pi Fusion automates and makes multi-model collaboration auditable by calling multiple independent models in parallel and then using a judge model to synthesize, validate, and report the findings.

Usage is straightforward: simply install the extension via the pi install command, then configure parameters such as participant models, the judge model, and the evidence backend using /pi-fusion-config. After setup, you can run the fusion panel with natural language instructions, e.g., /pi-fusion Should we migrate this module to a plugin architecture?. It will automatically schedule multiple models to generate answers in parallel, collect evidence, and finally output a report containing contradiction analysis and a final conclusion.

It is particularly suitable for teams or individuals requiring high-reliability decision-making, especially those already using the Pi framework to build agents and handle complex problems (such as architecture reviews, code reviews, product comparisons, or research analysis). Academic researchers can also use it to compare the performance of different models on the same task and obtain validated conclusions.

We recommend using this tool uniformly when weighing multiple options or avoiding bias from a single model. Note that it primarily relies on the Pi ecosystem, requires a Node.js environment, and participant and judge models must have their API keys pre-configured. Due to parallel calls to multiple models, token consumption and costs will increase accordingly. It is advisable to select --fast or --quality mode based on the importance of the task.