What are the system requirements for Delta Derivation?

The skill requires Claude Code, jq for JSON processing, and standard shell utilities like unzip and comm to process export files.

What is bisimulation verification in this context?

Bisimulation checks if two conversations are observationally equivalent by comparing their current state nodes and internal mapping lengths to detect if a thread has diverged or mutated.

What is a Claude.ai conversation delta?

A conversation delta is the difference in content, metadata, and structural state between two different point-in-time exports of your Claude.ai chat history.

How does this skill use Algebraic C-Sets (ACSets)?

It models conversations as objects in a schema-defined category, using injective morphisms to map the relationship between previous and recent exports for structural comparison.

Delta Derivation

Name: Delta Derivation
Author: plurigrid

byplurigrid

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Ciencia de Datos y ML

Extracts and verifies information deltas between Claude.ai conversation exports using categorical morphisms and bisimulation.

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Delta Derivation provides a rigorous mathematical framework for analyzing changes across Claude.ai conversation histories. By utilizing Algebraic C-Sets (ACSets) and bisimulation verification, it identifies new conversation threads, detects mutations in shared histories, and extracts skill usage patterns. This skill is essential for developers and AI researchers who need to track the evolution of their AI interactions with scientific precision, ensuring data integrity and measuring informational gain across multiple export versions using GF(3) triadic analysis.

Características Principales

2 GitHub stars
Bisimulation-based mutation detection for shared conversation IDs
Automated skill mention frequency tracking and trend analysis
GF(3) triadic analysis for compositional coherence and validation
Automated extraction and comparison of multiple Claude.ai ZIP exports
ACSets-driven structural analysis of message and node mappings

Casos de Uso

Tracking progress and structural changes between periodic Claude.ai backups
Verifying data integrity and identifying divergent branches in long-running AI threads
Analyzing the adoption and frequency of specialized skill invocations across projects

Acerca de

Características Principales

2 GitHub stars
Bisimulation-based mutation detection for shared conversation IDs
Automated skill mention frequency tracking and trend analysis
GF(3) triadic analysis for compositional coherence and validation
Automated extraction and comparison of multiple Claude.ai ZIP exports
ACSets-driven structural analysis of message and node mappings

Casos de Uso

Tracking progress and structural changes between periodic Claude.ai backups
Verifying data integrity and identifying divergent branches in long-running AI threads
Analyzing the adoption and frequency of specialized skill invocations across projects