# 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

```text
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.
knowledge_assets/  Stable long-term reusable knowledge distilled from local project artifacts.
ccra_review_bundle/  Per-round CCRA review packages; each round must live in its own dated subdirectory.
```

## 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 pass the local schema before they are treated as stable.

Validation should check:

- Required fields
- Enum values
- Unique model IDs
- Source article references
- Source evidence references
- Regression test references
- Model/card indexes
- Markdown card required sections
- Regression case coverage

## 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

Foundation repair in progress for:

- QPI
- Intellectual Archaeology / 思想考古学

Current foundation assets include:

- GPT plan localization protocol.
- File taxonomy for canonical, generated, review archive, and temporary files.
- Model extraction rules.
- Model card contract.
- Model extraction workflow.
- JSON schemas for model cards, source articles, source excerpts, regression cases, and indexes.
- Machine-readable model index.
- Human-readable card index.
- Validation scripts for model library contracts and card headings.
- Source article and source excerpt indexes.
- Regression cases for model use, boundary behavior, and misuse.
- Rule-based selector configuration and examples.
- A standard-library validation script that writes `reports/validation_report.md`.
- A standard-library index rebuild/check script that writes `reports/index_rebuild_report.md`.
- ChatGPT handoff rules.
- Long-term knowledge asset rules and `knowledge_assets/` documents, including `09_数据治理与模型调用机制说明.md`.

Current QPI and Intellectual Archaeology model contents pass the local contract and remain `draft` pending product review.

Indexes follow `docs/INDEX_MAINTENANCE_PROTOCOL.md`: every asset change must synchronize `models/model_index.json` and `cards/card_index.md`, and handoff/release points must run a full rebuild or check.

CCRA review packages are archived by round under `ccra_review_bundle/round-NN_YYYY-MM-DD_topic/`. Do not place new review bundle files directly in `ccra_review_bundle/`; create or update the current round directory instead.

## 13. Next Steps

1. Submit the Round 03.1 selector/no-call/regression patch for GPT / CCRA review.
2. Keep QPI and Intellectual Archaeology at `draft / B / pending` until Owner / CCRA review accepts stronger status.
3. Run a QPI blind-test round with new unlabelled inputs after Round 03.1 passes.
4. Defer any third-model expansion until the current QPI selector and case layer are accepted.
5. Route missing reusable extraction, inspection, or stability-scoring tools to `requirements/skills-vault/` or `requirements/ccpe/` instead of improvising local platform features.