What is SSL v0.2 format?

SSL (Symbolic Semantic Language) is a dense notation format that uses symbols like arrows (→) and triplets to represent logic, actions, and relationships without the token cost of verbose prose.

How does it handle uncertainty in data?

It uses specific symbolic markers, such as the '?' suffix for uncertain relationships and '!' prefix for negations, ensuring the nuances of the original data are captured.

Which Claude models work best with this skill?

High-intelligence models like Claude 3.5 Opus are recommended to ensure high-quality symbolic extraction and reconstruction. Smaller models like Haiku are discouraged for this task.

Does ε-Yajña lose important data during compression?

No. While it simplifies descriptive prose, it follows strict preservation rules for formulas, code, thresholds, and exact values, storing them verbatim in expansion hints.

ε-Yajña

Name: ε-Yajña
Author: genomewalker

bygenomewalker

0•

Ciencia de Datos y ML

Compresses verbose agent memories into a dense, symbolic format for efficient knowledge retrieval and context management.

ε-Yajña is a specialized utility designed for the cc-soul ecosystem that enables Claude to convert verbose natural language memories into the high-density SSL (Symbolic Semantic Language) v0.2 format. By utilizing a triplet-based structure and symbolic notation (→, +, @), it preserves critical insights, mathematical formulas, and code logic while significantly reducing token overhead. This skill acts as both an encoder and decoder, ensuring that complex domain knowledge is stored as reconstruction seeds that Claude can recognize and expand upon without the need for traditional prose parsers, making it ideal for managing long-term agent state and knowledge graphs.

Características Principales

01Lossless preservation of mathematical formulas and logic thresholds

02Parallel task processing for migrating legacy verbose documentation

03Automated memory node cleaning and 'ε-processed' tagging

04SSL v0.2 Encoding/Decoding for high-density symbolic storage

05Triplet extraction (Subject-Predicate-Object) for knowledge graph connectivity

060 GitHub stars

Casos de Uso

01Compressing extensive chat histories into structured, machine-readable knowledge nodes

02Optimizing AI context windows by replacing paragraphs with symbolic triplets and expansion hints

03Migrating legacy verbose developer documentation into high-density symbolic seeds

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add genomewalker/cc-soul epsilon-yajna

For use in Claude.ai and ChatGPT

Download Skill