Skip to main content
Glama
ginsonko

ap-aesthetics

by ginsonko

Related Servers

Alternatives to ap-aesthetics

No user-submitted related servers found.

    Related Servers

    • A
      license
      A
      quality
      B
      maintenance
      Enables prototyping, running, and evaluating typed judgment questions against TypeSafe's Jev model, including accuracy, calibration, and threshold analysis.
      3
      17 npm
      3
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables modeling cumulative sleep deficits, estimating cognitive impairment through PVT attention lapses and BAC equivalence, auditing social jetlag, and generating circadian-safe gradual sleep repayment schedules.
      7
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables users to model cumulative sleep deficits, estimate cognitive impairment using Van Dongen PVT kinetics, audit social jetlag, and generate circadian-safe gradual sleep repayment schedules.
      7
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables users to calculate circadian phase angles of entrainment, score internal circadian desynchrony, and derive photic PRC-based advance, delay, and curfew guidance from biomarker and sleep schedule inputs.
      7
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Provides a measured reading pipeline for AI readers of historical handwritten and typed records, with tools for inspection, evidence extraction, comparison, and Brier-scored calibration.
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      A zero-dependency MCP suite exposing computational tools across metabolic, cardio-renal, chronobiology, neuro-recovery, and biomechanics domains. It enables clients to derive longevity and physiology metrics such as autophagy index, glucose-ketone ratio, glycemic variability, peripheral resistance, nocturnal BP dipping, DLMO clock time, melanopic lux, caffeine clearance, EEG fatigue entropy, and grip vitality age from user-supplied measurements.
      7
      MIT

    TDQS

    B3.2/5.0

    Scored across 10 tools

    Disambiguation4/5

    Each tool has a distinct verb+object focus: evaluate vs compare vs sensitivity vs audience_panel are separable evaluation modes, and fit/apply/tune form distinguishable calibration steps. Mild overlap among the evaluation tools (ap_evaluate, ap_compare, ap_sensitivity) is resolved by explicit descriptions.

    Naming Consistency4/5

    All names share a consistent ap_ prefix and are snake_case, but the pattern mixes noun forms (ap_catalog, ap_template, ap_audience_panel, ap_sensitivity) with verb-based forms (ap_evaluate, ap_fit_calibration, ap_tune_parameters). Readable and predictable overall, just not uniformly verb_noun.

    Tool Count5/5

    Ten tools is well within the ideal 3-15 range and each maps to a distinct capability in the evaluation/calibration pipeline. No redundant or filler tools are apparent.

    Completeness4/5

    The surface covers a full workflow: reference lookup, templating, evaluation, comparison, panel, sensitivity, dataset inspection, and fit/apply/tune calibration. Minor gaps around persistence/export of results, but core lifecycle is intact.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues