analyze-scaling-regime

SkillMonitoring & ops

Lets your agent analyze claude skill results for scaling trends, regime shifts, and saturation across a scale variable.

Use analyze-scaling-regime in Claude, ChatGPT or Ahel Desktop

Free. Sign in, add analyze-scaling-regime and connect your AI. About a minute.

Also: Claude Code · Cursor · Codex

Then ask your AI: use the analyze-scaling-regime skill

Details

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Add Ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

analyze-scaling-regimeStart free
About this skill

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

What this skill tells your AI

The instructions your AI receives, as published by yogsoth-ai/de-anthropocentric-research-engine in skills/analyze-scaling-regime/SKILL.md and read by Ahel’s review.

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.

Signals

GitHub stars
503
Forks
42
Last commit
Sep 2026
Advanced
Item type
skill
Key
analyze-scaling-regime
Source
github.com/yogsoth-ai/de-anthropocentric-research-engine