classify-simplicity-evidence
SkillDev toolsLets your agent judge whether an explanation's simplicity is genuinely informative or just a relabeling.
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 classify-simplicity-evidence skill
About this skill
Classify simplicity/compression as earned, weak, or decorative based on whether it forbids alternatives, compresses independent facts, or merely renames/repackages them.
What this skill tells your AI
The instructions your AI receives, as published by yogsoth-ai/de-anthropocentric-research-engine in skills/classify-simplicity-evidence/SKILL.md and read by ahel’s review.
Purpose
Classify explanatory compression as earned, weak, or decorative.
Input contract
required: [explanation, covered_facts, alternatives, predictions]
optional: [evidence]
constraints: [facts and alternatives must be independently listed]
Procedure
- Check whether independent facts are compressed.
- Check whether alternatives are forbidden and predictions constrained.
- Classify earned, weak, or decorative and preserve rationale.
If simplicity provides discriminating support only through a vulnerable consequence, consider test-risky-prediction as the next tactic.
Output contract
produces: [simplicity_class, compression_evidence, missing_constraints]
delta_fields: [findings, evidence_updates, uncertainties, decisions]
Quality gates
- Decorative simplicity is a relabeling with no independent compression or risky prediction.
Failure and counterexamples
Do not classify by description length or elegance alone.
Provenance map
- resolved: elegance-trap-probe
Signals
- GitHub stars
- 501
- Forks
- 41
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Key
classify-simplicity-evidence- Source
- github.com/yogsoth-ai/de-anthropocentric-research-engine