progress-curve-fitting

Business

Construct performance-over-time visualization data

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How to use this skill

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Progress Curve Fitting

Purpose

Fit parametric curves to historical SOTA performance data, identify inflection points representing paradigm shifts, and extrapolate future progress trajectories. Produces structured data suitable for visualization and trend analysis.

Input Schema

Field	Type	Description
historical_scores	object[]	Array of {method, score, date, dataset, metric} sorted chronologically

Output Schema

{
  "dataset": "string",
  "metric": "string",
  "time_range": {"start": "string", "end": "string"},
  "sota_frontier": [
    {"date": "string", "method": "string", "score": 0.0, "is_new_sota": true}
  ],
  "curve_fit": {
    "best_model": "logarithmic|linear|sigmoid|exponential|piecewise",
    "parameters": {},
    "r_squared": 0.0,
    "residual_std": 0.0
  },
  "inflection_points": [
    {
      "date": "string",
      "method": "string",
      "score_before": 0.0,
      "score_after": 0.0,
      "jump_magnitude": 0.0,
      "paradigm_shift": "string"
    }
  ],
  "trend_metrics": {
    "annual_improvement_rate": 0.0,
    "improvement_accelerating": false,
    "years_since_last_major_jump": 0.0,
    "current_plateau_duration": null
  },
  "extrapolation": {
    "predicted_1yr": 0.0,
    "predicted_3yr": 0.0,
    "confidence_band_1yr": [0.0, 0.0],
    "confidence_band_3yr": [0.0, 0.0],
    "caveat": "string"
  }
}