Agent skill

Analyze Scaling Regime

by yogsoth-ai in yogsoth-ai/de-anthropocentric-research-engine

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

Apache-2.0Auto-check passed

Install Analyze Scaling Regime

skills CLI
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill analyze-scaling-regime -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install yogsoth-ai/de-anthropocentric-research-engine analyze-scaling-regime --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/yogsoth-ai/de-anthropocentric-research-engine.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/analyze-scaling-regime .claude/skills/analyze-scaling-regime && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
analyze-scaling-regime
GitHub stars
505
Token cost
~502 tokens
SKILL.md length
162 words
Files
1
Skills in repo
12
Repo updated
First seen
Licence
Apache-2.0

At a glance

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

  • Works in 4 steps: Normalize scale and outcome definitions… → Plot or tabulate local behavior and fit… → Locate qualitative shifts, saturation,… → …
  • SKILL.md covers Purpose, Input contract, Procedure and Output contract, plus 5 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Analyze Scaling Regime is an agent skill from yogsoth-ai/de-anthropocentric-research-engine. Analyze how conclusions/performance change across scale and identify regime shifts, saturation, power-law/log-law behavior, or frontier transitions.

Its SKILL.md is about 500 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The repository describes itself as: A 267-skill research graph in pure markdown — 51 research operations built from 216 single-purpose steps, composed in any order with explicit backtracking. One npx install, no… The licence is Apache-2.0.

Example prompts

  • “/analyze-scaling-regime”

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  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.

What it can do on your machine

Read from SKILL.md and the folder at commit bdb3524. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are yaml).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Analyze Scaling Regime loads about 502 tokens when it runs. Until then it costs about 43 tokens; SKILL.md has 162 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~43
When it runs · the whole SKILL.md, loaded when a task matches
~502

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from yogsoth-ai/de-anthropocentric-research-engine at commit bdb3524, republished under its Apache-2.0 licence (© yogsoth-ai). 162 words, ~502 tokens.

Download SKILL.mdSave it as .claude/skills/analyze-scaling-regime/SKILL.md (or your agent's skills folder).
name
analyze-scaling-regime
description
Analyze how conclusions/performance change across scale and identify regime shifts, saturation, power-law/log-law behavior, or frontier transitions.

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

yaml
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

yaml
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.

© yogsoth-ai, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/analyze-scaling-regime of yogsoth-ai/de-anthropocentric-research-engine.

Open the folder on GitHubat commit bdb3524

Compare with similar skills

Analyze Scaling Regime next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Analyze Scaling Regime compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Analyze Scaling Regime this skillyogsoth-ai/de-anthropocentric-research-engine505—~502Automated safety check: PassApache-2.0
Trader Regimeruvnet/ruflo74k—~408Automated safety check: NotesMIT
Scale Benchmarkssickn33/agentic-awesome-skills47k1 repos~1.4kAutomated safety check: PassMIT
Qdrant Scalinggithub/awesome-copilot40k1 repos~467Automated safety check: PassMIT
Idea Scale AutomationComposioHQ/awesome-claude-skills77k3 repos~742Automated safety check: PassNone
Correlation Regime DetectionHKUDS/Vibe-Trading35k—~5.4kAutomated safety check: PassMIT

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Questions about Analyze Scaling Regime

What does Analyze Scaling Regime do?

Analyze how conclusions/performance change across scale and identify regime shifts, saturation, power-law/log-law behavior, or frontier transitions. Analyze Scaling Regime is an agent skill from yogsoth-ai/de-anthropocentric-research-engine. Analyze how conclusions/performance change across scale and identify regime shifts, saturation, power-law/log-law behavior, or frontier transitions.

How do I install Analyze Scaling Regime in Claude Code?

Run `npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill analyze-scaling-regime -a claude-code`. Or copy the skill folder (skills/analyze-scaling-regime in yogsoth-ai/de-anthropocentric-research-engine) into .claude/skills/analyze-scaling-regime in your project. Claude Code loads it when a task matches its description.

How do I install Analyze Scaling Regime in Codex?

Run `npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill analyze-scaling-regime -a codex`. Or copy the skill folder (skills/analyze-scaling-regime in yogsoth-ai/de-anthropocentric-research-engine) into .agents/skills/analyze-scaling-regime in your project. Codex loads it when a task matches its description.

Can I use Analyze Scaling Regime in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill analyze-scaling-regime -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/analyze-scaling-regime, .gemini/skills/analyze-scaling-regime, .github/skills/analyze-scaling-regime and .opencode/skills/analyze-scaling-regime in your project.

What does Analyze Scaling Regime need to run?

SKILL.md names no scripts, command-line tools or credentials: Analyze Scaling Regime is instructions for the agent only.

Does Analyze Scaling Regime access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Analyze Scaling Regime safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Analyze Scaling Regime use?

Analyze Scaling Regime is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Analyze Scaling Regime use?

About 502 tokens (SKILL.md is roughly 2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Analyze Scaling Regime?

Skills that share tags, products or a category with Analyze Scaling Regime: Trader Regime (ruvnet/ruflo, 74k stars), Scale Benchmarks (sickn33/agentic-awesome-skills, 47k stars), Qdrant Scaling (github/awesome-copilot, 40k stars) and Idea Scale Automation (ComposioHQ/awesome-claude-skills, 77k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Analyze Scaling Regime?

yogsoth-ai (a GitHub organization) maintains it in yogsoth-ai/de-anthropocentric-research-engine, which has 505 GitHub stars. The repository holds 12 skills in this directory. The repository was last updated on September 29, 2026.

Source: yogsoth-ai/de-anthropocentric-research-engine on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.