characterize-anomaly

SkillDev tools

Lets your agent rigorously analyze an unexpected observation by comparing it to expectations and ruling out trivial causes.

Available today. Use it from your connected AI after setup.

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 characterize-anomaly skill

About this skill

Precisely characterize an anomaly by contrasting observation with expectation, quantifying deviation where possible, recording conditions, and excluding obvious/trivial explanations before generating hypotheses.

What this skill tells your AI

The instructions your AI receives, as published by yogsoth-ai/de-anthropocentric-research-engine in skills/characterize-anomaly/SKILL.md and read by ahel’s review.

Purpose

Characterize an observation that departs from an expected pattern and separate signal from measurement or protocol artifact.

Input contract

required: [observation, reference_pattern, condition_records]
optional: [uncertainty_estimates, replication_records, artifact_hypotheses]
constraints: [anomaly status requires a defined comparison and condition context]

Procedure

  1. Define the expected pattern and comparison basis.
  2. Quantify the departure with uncertainty and condition alignment.
  3. Test plausible data, protocol, and mechanism explanations.
  4. Classify the anomaly and identify discriminating follow-up evidence.

If the anomaly is reproducible and not explained by a recording artifact, consider generate-competing-hypotheses as the next tactic.

Output contract

produces: [anomaly_description, comparison_basis, explanation_set, discriminating_evidence]
delta_fields: [findings, evidence_updates, uncertainties, recommended_jumps]

Quality gates

  • The reference pattern and departure measure are explicit.
  • Artifact explanations are checked before causal interpretations.

Failure and counterexamples

Do not label a rare value anomalous without a comparison distribution or ignore changed measurement conditions.

Provenance map

  • resolved: characterize-anomaly

Signals

GitHub stars
501
Forks
41
Last commit
Sep 2026
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Catalog kind
skill
Key
characterize-anomaly
Source
github.com/yogsoth-ai/de-anthropocentric-research-engine