cognitive-surrogate

Build psychological profiles from interaction data and predict cognitive trajectories.

60|13|Updated Dec 22, 2025
One-click install
npx skills add https://github.com/plurigrid/asi --skill cognitive-surrogate
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: cognitive-surrogate
Source: https://github.com/plurigrid/asi/tree/main/skills/cognitive-surrogate
Command: npx skills add https://github.com/plurigrid/asi --skill cognitive-surrogate

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires gay-mcp, acsets, bisimulation-game.

What problem does it solve?

The Cognitive Surrogate Skill enables building high-fidelity psychological models from interaction data. It extracts values, predicts cognitive trajectories, and generates authentic responses that preserve the subject's voice with high fidelity.

Core Principle: A surrogate is a derivational continuation of cognition, not a surface imitation.

NEW (Langevin/Gibbs Integration): Predictions leverage a Gibbs distribution; confidence scores reflect mixing time and temperature parameters.

Core Capabilities

  1. build-psychological-profile
  2. train-predictor
  3. validate-fidelity
  4. generate-authentic-reply
  5. predict-via-gibbs-distribution (NEW)
  6. project-trajectory

Integration: ethics & safety

  • Explicit subject consent for surrogates
  • Transparent disclosure when surrogate-generated content is used
  • Boundaries on high-stakes decisions
  • Audit trail with seeds for reproducibility

Quick Start

Initialize a seed, build a profile from your interaction corpus, train a predictor, and generate an authentic reply.

Frequently Asked Questions about cognitive-surrogate

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build psychological models from interaction data?▼

Psychological models extract values and predict cognitive trajectories from interaction patterns. Initialize a seed, build a profile from your dialogue corpus or interaction logs, train a predictor, and generate authentic replies that preserve the subject's voice with >90% fidelity.

What is a cognitive surrogate and how does it differ from surface imitation?▼

A cognitive surrogate is a derivational continuation of cognition, not a surface imitation. It reconstructs psychological patterns from interaction data to generate predictions and responses grounded in the subject's actual reasoning patterns.

Can I use Gibbs distributions for confidence scoring in surrogate predictions?▼

Yes. The Langevin/Gibbs integration enables predictions that leverage Gibbs distributions, with confidence scores reflecting mixing time and temperature parameters for more precise uncertainty quantification.

How do I validate that a surrogate model maintains high fidelity?▼

Validation is configurable and meets functional requirements such as >90% fidelity in predictions. Build your profile, train the predictor, then run validate-fidelity against held-out interaction data to measure prediction accuracy.

What governance and safety features are built in for surrogate models?▼

Built-in governance includes explicit subject consent, transparent disclosure when surrogate-generated content is used, boundaries on high-stakes decisions, and audit trails with seeds for reproducibility.

Does this work with dialogue corpora and consented research contexts?▼

Yes. The Skill applies across dialogue corpora, interaction logs, and consented research contexts. It integrates data extraction pipelines via DuckDB and multi-interpreter support for flexible input handling.