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The Mindscape of Bro Tsong

Project: The Mindscape of Bro Tsong

Current phase: model_library_mvp

Current subsystem: Model Library / Model Management MVP

1. Project Definition

This project is a file-first MVP for a cognitive model library.

It turns core cognitive models into structured, traceable, callable, and testable model assets.

The first version validates the workflow with two sample models:

  • QPI
  • Intellectual Archaeology

2. What This Project Is

This project is:

  • A model asset library
  • A model card system
  • A source evidence index
  • A regression test container
  • A minimal model selection demo foundation
  • A foundation for a future question-answering / cognitive processing system

3. What This Project Is Not

This project is not:

  • A full model management platform
  • A public SaaS product
  • A user-facing application
  • A complete knowledge graph
  • A full RAG system
  • A commercial platform
  • A multi-user collaboration system
  • A complete question-answering system

4. Current MVP Goal

The current MVP tests whether a small number of core cognitive models can be represented as:

  • Human-readable model cards
  • Machine-readable JSON model specs
  • Source article records
  • Source evidence excerpts
  • Regression test cases
  • Minimal selector inputs and outputs

5. First Sample Models

QPI

QPI is a routing model that classifies a user input as:

  • Question: lack of information
  • Problem: lack of path or method
  • Issue: lack of stability, consensus, or dynamic balance

Intellectual Archaeology

Intellectual Archaeology is a deep modeling model that analyzes a topic through multiple depth layers, from surface application to mechanism, purpose, human capability, and philosophical assumptions.

6. Repository Structure

docs/      Project rules, contracts, workflow notes, decisions, non-goals, and handoff templates.
schemas/   JSON Schema files for model specs, source records, source excerpts, and regression cases.
models/    Machine-readable JSON model specifications.
cards/     Human-readable Markdown model cards.
sources/   Source article records and source evidence excerpts.
tests/     Regression cases for model use, misuse, and boundary checks.
selector/  Rule-based selector configuration and examples.
scripts/   Local validation and selector demo scripts.
reports/   Validation reports, extraction notes, and concrete session handoffs.

7. Data Format

The project uses JSON as the machine-readable source format.

Markdown files are used for human-readable model cards and documentation.

8. Validation

All model JSON files should eventually pass schema validation.

Validation should check:

  • Required fields
  • Enum values
  • Unique model IDs
  • Source article references
  • Source evidence references
  • Regression test references

9. Minimal Selector

The selector is not a full AI system.

It is a simple demo that recommends candidate models based on:

  • Trigger keywords
  • Input type match
  • Negative triggers
  • Pipeline position
  • Selection priority

10. Development Principles

  • Keep the MVP small.
  • Prefer files over databases.
  • Prefer explicit schema over implicit conventions.
  • Prefer traceability over automation.
  • Prefer testability over expressive writing.
  • Do not expand to many models before the sample models are stable.
  • Treat model_library_mvp as the current phase, not as a nested project root.

11. Related Projects

  • knowledge-vault: source archive, discussion records, and durable upstream documentation.
  • ccpe-system: expert-agent, runtime, model, and protocol specification workbench.
  • skills-vault: canonical source for reusable automation skills.
  • writing-workbench: deep writing production workspace.
  • video-workbench: dimensional output workspace for scripts, presentations, and videos.

This repository consumes selected source material and model definitions from the surrounding ecosystem, but it remains the product/system boundary for The Mindscape of Bro Tsong.

See PROJECTS.md for the operative cross-repository boundary map, including request channels for ccpe-system and skills-vault.

12. Current Status

Initial project setup.

13. Next Steps

  1. Confirm directory structure.
  2. Confirm schema files.
  3. Add QPI model JSON.
  4. Add Intellectual Archaeology model JSON.
  5. Add human-readable model cards.
  6. Add source records and evidence excerpts.
  7. Add regression cases.
  8. Add validation scripts.
  9. Add minimal selector demo.