Which programming languages does this skill utilize?

The skill provides a multi-interpreter approach, using Julia (ACSets) for schema modeling, Python (DuckDB) for profile building, Ruby for condensed mathematics integration, and Hy for behavioral pattern extraction.

How is the fidelity of the surrogate measured?

Fidelity is measured across four key metrics: topic prediction (>85%), semantic similarity (>90%), style consistency (>88%), and value alignment (>92%), targeting a weighted average of over 90%.

What is a Cognitive Surrogate in the context of this skill?

A Cognitive Surrogate is a high-fidelity model that learns the generative grammar of a subject's cognition rather than just imitating surface patterns, allowing for authentic response generation and trajectory prediction.

What ethical safeguards are included in this skill?

The skill enforces explicit consent protocols, mandatory disclosure of surrogate-generated content, refusal boundaries for high-stakes decisions, and a subject-controlled kill switch for model invalidation.

Cognitive Surrogate Engine

Name: Cognitive Surrogate Engine
Author: plurigrid

byplurigrid

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데이터 과학 및 ML

Constructs high-fidelity psychological models from interaction patterns to predict intellectual trajectories and maintain authentic voice consistency.

The Cognitive Surrogate skill is a sophisticated modeling engine designed to build 'derivational continuations' of cognition rather than simple surface imitations. By utilizing a multi-language stack including Julia for category-theoretic structures and Python for data extraction, it enables developers to create psychological profiles with over 90% fidelity. This skill is particularly useful for researchers and developers building advanced agentic systems that require deep persona consistency, ethical boundary modeling, and behavioral prediction based on structured interaction corpora.

주요 기능

012 GitHub stars

02Automated value and interest extraction from DuckDB interaction corpora

03High-fidelity psychological modeling with >90% accuracy targets

04Comprehensive fidelity metrics for style, values, and semantic similarity

05Category theory-based profile structuring using ACSets

06Multi-language integration supporting Julia, Python, Ruby, and Hy

사용 사례

01Validating AI agent behavior against specific human interaction datasets

02Building authentic digital twins for longitudinal psychological research

03Predicting subject-specific cognitive trajectories in educational simulations

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add plurigrid/asi cognitive-surrogate

For use in Claude.ai and ChatGPT

Download Skill