科研 agent 平台用类 Jev 决策模型砍半 token 成本
一个科研 agent 平台接入 294 个连接器和 200+ 技能，用本体化组织和类 Jev 决策模型选择工具，token 成本减半且调用准确率提升。
Ahem ahem. Topic: Own and Customize everything 294 Connectors across target science, mol engineering, developmental biology. DBs, tools, atlases, just ask for it. You can add custom ones. 200+ skills along the same lines. Add custom skills. Give permissions to all the platform workflows. Add custom instructions, give permissions what your agents can and can not use and when to ping you. Even create your own subagents. Compute: Select the compute capacity you need when agentic coding requires gpus. We have found ways where we have ontologically organized every connector and skill, use jev-like decision models, and cut the token cost by half, and actually getting better accuracy in using the right things in the right time. As said before, if we are going to do agentic science, lets do it in a right, controlled way, just like how controlled reproducible experiments looks like.
这条是引用着另一条写的：x.com/anindyadeeps/status/2114061288276144449