What is the primary purpose of the Cognitive Surrogate skill?

It builds high-fidelity psychological models from interaction data to predict cognitive trajectories and generate authentic, voice-consistent responses.

How does this skill achieve >90% fidelity?

By focusing on the 'generative grammar' of cognition rather than surface patterns, using advanced mathematical frameworks like ACSets and condensed mathematics.

Which programming languages are supported for profile building?

The skill integrates with Julia for schema definition, Python for data extraction, Ruby for sheaf-based structures, and Hy for behavioral analysis.

Are there ethical safeguards included with this skill?

Yes, it includes strict protocols for subject consent, mandatory disclosure of AI content, audit trails for reproducibility, and a manual kill switch.

Cognitive Surrogate

Name: Cognitive Surrogate
Author: plurigrid

byplurigrid

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Data Science & ML

Builds, trains, and validates high-fidelity psychological models from interaction patterns to predict cognitive trajectories and generate authentic responses.

The Cognitive Surrogate skill is a sophisticated Layer 6 Barton tool designed to construct psychological models with over 90% fidelity. By extracting structured data—including values, interests, and behavioral patterns—from interaction corpora, it enables the creation of 'derivational continuations' of specific personas. It leverages a multi-language stack (Julia, Python, Ruby, and Hy) to analyze cognitive generative grammars rather than just surface-level imitation, making it ideal for creating sophisticated AI personas, testing user behavior scenarios, and preserving authentic voices in digital interactions while maintaining strict ethical boundaries.

Key Features

017 GitHub stars

02Integration with GF(3) Triad for coordinated self-validation and deterministic seeding.

03High-fidelity psychological profiling with >90% accuracy in topic prediction and semantic similarity.

04Multi-interpreter support for Julia (ACSets), Python (DuckDB), and Ruby (sheaf-based profiles).

05Advanced behavioral pattern extraction using entropy-maximized analysis and HyJAX.

06Comprehensive ethical framework including consent protocols and mandatory disclosure rules.

Use Cases

01Developing high-accuracy digital twins for user experience testing and behavioral prediction.

02Preserving authentic expert or historical voices for educational simulations and research.

03Constructing AI agents with consistent ethical frameworks and predictable intellectual trajectories.

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