analyze-scaling-regime
SkillMonitoring & opsLets your agent analyze claude skill results for scaling trends, regime shifts, and saturation across a scale variable.
Available today. Use it from your connected AI after setup.
No other account needed.
Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
Then ask your AI: use the analyze-scaling-regime skill
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
- Normalize scale and outcome definitions while retaining original units.
- Plot or tabulate local behavior and fit only caller-authorized within-regime models.
- Locate qualitative shifts, saturation, or frontier transitions and test their stability.
- 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
| source | criterion |
|---|---|
| scaling-frontier | Analyze behavior across scales, detect regime changes, and identify capacity limits and mechanisms. |
Signals
- GitHub stars
- 501
- Forks
- 41
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Key
analyze-scaling-regime- Source
- github.com/yogsoth-ai/de-anthropocentric-research-engine