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analyze-scaling-regime

Skill504 starsChanged 50 days agoApache-2.0View on GitHub

Analyze how conclusions/performance change across scale and identify regime shifts, saturation, power-law/log-law behavior, or frontier transitions.

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SKILL.md

analyze-scaling-regime

Purpose

Analyze how conclusions or performance change across scale and identify regime shifts, saturation, scaling-law behavior, or frontier transitions.

Input contract

required: [scale_variable, outcome_series, observation_context]
optional: [candidate_scaling_laws, uncertainty_model, suspected_breakpoints]
constraints: [scale units and outcome direction must be explicit; observations remain ordered]

Procedure

  1. Normalize scale and outcome definitions while retaining original units.
  2. Plot or tabulate local behavior and fit only caller-authorized within-regime models.
  3. Locate qualitative shifts, saturation, or frontier transitions and test their stability.
  4. Report regime boundaries, mechanism hypotheses, and extrapolation limits.

Output contract

produces: [regime_map, breakpoint_candidates, scaling_diagnostics, extrapolation_limits]
delta_fields: [findings, evidence_updates, uncertainties, open_questions]

Quality gates

  • Each claimed regime has observations on both sides or is marked extrapolative.
  • Breakpoints include uncertainty or sensitivity information.
  • Power-law/log-law labels are supported by fit diagnostics, not visual slope alone.

Parameterization

Caller supplies scale axis, outcome schema, candidate laws, breakpoint rule, fit diagnostics, and acceptable extrapolation distance.

Failure and counterexamples

Reject a regime claim based on a single point or a scale change confounded with protocol change.

Provenance map

  • resolved: scaling-frontier
  • concept: deep-insight/scaling-analysis

Preserved source criteria ledger

sourcecriterion
scaling-frontierAnalyze behavior across scales, detect regime changes, and identify capacity limits and mechanisms.

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