def METHOD_NAME(fm):
    rc = fm.reduced_chi2
    s_ncall = f"Nfcn = {fm.nfcn}"
    if fm.ngrad > 0:
        s_ncall += f", Ngrad = {fm.ngrad}"
    if fm.hesse_failed:
        covariance_msg1 = "Hesse FAILED"
        if fm.has_reached_call_limit:
            covariance_msg2 = "ABOVE call limit"
        else:
            assert not fm.has_posdef_covar
            covariance_msg2 = "Covariance NOT pos. def."
    else:
        if fm.has_covariance:
            covariance_msg1 = "Hesse ok"
            if fm.has_accurate_covar:
                covariance_msg2 = "Covariance accurate"
            elif fm.has_made_posdef_covar:
                covariance_msg2 = "Covariance FORCED pos. def."
            else:
                covariance_msg2 = "Covariance APPROXIMATE"
        else:
            covariance_msg1 = "Hesse not run"
            covariance_msg2 = "NO covariance"
    return [
        f"{fm.algorithm}",
        f"FCN = {fm.fval:.4g}" + (f" (χ²/ndof = {rc:.1f})" if not np.isnan(rc) else ""),
        s_ncall,
        f"EDM = {fm.edm:.3g} (Goal: {fm.edm_goal:.3g})",
        f"time = {fm.time:.1f} sec" if fm.time >= 0.1 else "",
        f"{'Valid' if fm.is_valid else 'INVALID'} Minimum",
        f"{'ABOVE' if fm.is_above_max_edm else 'Below'} EDM threshold (goal x 10)",
        f"{'SOME' if fm.has_parameters_at_limit else 'No'} parameters at limit",
        f"{'ABOVE' if fm.has_reached_call_limit else 'Below'} call limit",
        covariance_msg1,
        covariance_msg2,
    ]