sophia

Solid

Discover your philosophical tradition through behavioral dimension analysis and philosopher matching.

AI & Automation 125 stars 11 forks Updated today MIT

Install

View on GitHub

Quality Score: 81/100

Stars 20%
70
Recency 20%
100
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
50
License 10%
100
Description 5%
100

Skill Content

# Sophia (σοφία) Discover your philosophical tradition through behavioral pattern analysis. > φιλο-σοφία = "love of wisdom" > Your conversation patterns carry the fingerprint of a philosophical tradition. ## When to Use Invoke this skill when: - Exploring which philosophical tradition your AI conversation patterns resemble - Analyzing behavioral dimensions across sessions for epistemic style profiling - Generating a visual philosopher match profile card Skip when: - Analyzing strengths and structural costs (use /curses instead) - Quick single-protocol question (answer directly) - No session history exists and user prefers manual exploration ## Pipeline | Phase | What | Mode | |-------|------|------| | 1. Collect | Gather behavioral data from sessions | dimension-profiler agent | | 2. Match | Map dimension profile to philosophers | AI analysis | | 3. Present | Dual-layer result + protocol affinity | Gate interaction | | 4. Report | Generate HTML profile card | Automated | --- ## Phase 1: Data Collection **Same-session reuse**: If dimension-profiler output is already available in this conversation (from a prior `/sophia` or `/curses` run), skip Phase 1 entirely and reuse that output. Both skills produce identical profiler results. Two-step delegation: first run `coverage-scanner` for pre-aggregated data, then pass the result to `dimension-profiler` for dimension scoring. This avoids duplicate file reading and gives the profiler access to protocol usage counts. **Ste...

Details

Author
jongwony
Repository
jongwony/epistemic-protocols
Created
7 months ago
Last Updated
today
Language
JavaScript
License
MIT

Bundled in these plugins

Similar Skills

Semantically similar based on skill content — not just same category