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spec-patterns

Identify recurring patterns and themes from text data into clusters and cards.

Updated Dec 19, 2025
Search Tags:#patterns#insights#themes#knowledge-graph#clustering#data-visualization#pattern-analysis
One-click install
npx skills add https://github.com/float-ritual-stack/floatty --skill spec-patterns
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: spec-patterns
Source: https://github.com/float-ritual-stack/floatty/tree/main/apps/outline-explorer/src/lib/skills/spec-patterns
Command: npx skills add https://github.com/float-ritual-stack/floatty --skill spec-patterns

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Patterns are often buried in text data. This Skill exposes recurring themes and clusters to help teams derive actionable insights.

Core Features & Use Cases

  • PatternClustering: group similar items into thematic clusters with cross-connections.
  • PatternCard & Paragraph: present themes as concise cards with syntheses.
  • Use Case: analyze user feedback or interview transcripts to surface dominant themes and their relationships.

Quick Start

Provide a dataset of items and run the Patterns action to generate clusters and theme cards

Frequently Asked Questions about spec-patterns

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I identify recurring themes in interview transcripts?▼

You can surface dominant themes in user feedback by grouping similar items into thematic clusters and presenting syntheses as concise pattern cards with cross-connections.

What is pattern clustering for text data?▼

Pattern clustering for text data is a mechanism that groups similar items from sources like research notes or product reviews into thematic clusters to expose recurring patterns and relationships.

Does pattern analysis work for product reviews and research notes?▼

Pattern analysis works for product reviews and research notes by processing the provided text dataset to extract and visualize recurring themes as structured clusters and cards.

How do I group user feedback into thematic clusters?▼

You group user feedback into thematic clusters by providing the dataset of items and running the analysis action, which organizes the text into grouped themes and concise card syntheses.

What components are needed to structure pattern analysis output?▼

Structuring pattern analysis output requires support for components such as SectionLabel, PatternCluster, PatternCard, Paragraph, and ConfidenceDot to organize themes and visualizations.

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