Testing Grok agents built around separate thinking methods
Grok is being tested in a more agent-like setup where custom skills act as small, specialized reasoning modules. Each skill focuses on a thinking method, such as first-principles analysis, , , second-order effects, , probabilistic thinking, Occam’s Razor, Hanlon’s Razor, margin of safety, circle of competence, and inversion for finding failure points. The aim is to make answers to complex or unclear questions more structured, easier to inspect, and less likely to include made-up reasoning.
The setup also includes one combined mental-model toolkit and explainers that adapt to the audience or situation. connects parallel tool calls, web research, code execution, file work, and or editing so the work can produce repeatable artifacts. External services such as GitHub, Notion, and Gmail are part of the planned end-to-end workflow.
keeps context, preferences, and project state across sessions so the same background does not need to be repeated every time.
Key points
- Custom skills in Grok are used like specialized reasoning agents.
- The skills map to thinking methods such as first-principles analysis and .
- covers parallel tool calls, web research, code execution, file work, and image work.
- GitHub, Notion, and Gmail are mentioned as possible external service integrations.
- may cut repeated explanations, which can help reduce token use.