Builds an autonomous iterative research loop that narrows a wide uncertainty/exposure range toward a user-defined target by issuing Google searches, extracting evidence from results, re-estimating the range from accumulated evidence, and repeating until converged. Use when the user wants to implement autonomous research that progressively reduces uncertainty toward a quantified goal — risk analysis, market sizing, due diligence, literature review, or any domain where a wide estimate must be narrowed with real evidence.

Iteratively optimize thermal designs by solving 2D heat equations (Poisson PDE). Parameterize heat source placement and material conductivity, simulate temperature distributions, evaluate performance metrics, and propose improvements autonomously. Use when the user asks to design, optimize, or analyze heat sinks, thermal layouts, cooling systems, or any steady-state thermal problem on a 2D domain.