Agent skill · data analytics · aiskillstore
reasoning-inductive
Extract patterns and generalizations from multiple observations. Use when detecting recurring themes, building predictive rules, or identifying systemic behaviors from accumulated data. Produces validated patterns with confidence bounds and exception handling.
Why this skill is useful
Provides a structured approach to extract patterns and generalizations from data that the AI wouldn't reliably generate on its own.
What it needs
About 7k tokens when loaded. Last updated 2026-08-07. 405 stars on the source repository.
What this skill does
Inductive Reasoning Generalize from instances to rules. The logic of pattern extraction and empirical learning. Type Signature When to Use Use inductive when: Multiple similar observations accumulate Looking for recurring patterns across threads Building predictive rules from experience Identifying systemic behaviors Validating or discovering Canvas assumptions "This keeps happening" situations Don't use when: Explaining single observation → Use Abductive Known causal chain exists → Use Causal Transferring one case to another → Use Analogical Resolving disagreement → Use Dialectical Distinction from Other Modes Mode Input Output Question ------ ------- -------- ---------- Abductive Single anomaly Explanation "Why did this happen?" Inductive Multiple instances Pattern/Rule "What keeps happening?" Analogical One source case Transferred solution "How is this like that?" Key difference from Abductive: Abductive: 1 observation → 1 explanation Inductive: N observations → 1 generalization Four-Stage Process Stage 1: Observation Collection Purpose: Gather and structure multiple instances for analysis. Minimum Sample Requirements: Confidence Target Minimum N Notes ------------------- ----------- ------- Exploratory 3-5 Hypothesis generation only Tentative 6-10 Directional confidence Moderate 11-20 Actionable patterns High 21+ Strong generalizations Components: Stage 2: Pattern Detection Purpose: Identify regularities in the dataset. Pattern Types: Type Description Example ------ ------------- --------- Frequency How often X occurs "7/12 deals stall at legal" Correlation X and Y co-occur "Large deals AND long cycles" Sequence X follows Y "Stall → lose within 30 days" Cluster Groups emerge "Two deal archetypes exist" Trend Direction over time "Cycles getting longer" Threshold Breakpoint exists "Deals >$300K behave differently" Detection Process: Stage 3: Generalization Purpose: Form rules from validated patterns. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills aiskillstore/reasoning-inductive