chore: initialize model library mvp

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 # AGENTS.md
 ## 1. Role
 You are Codex working inside the `the-mindscape-of-bro-tsong` repository.
 Your role is to implement the engineering structure for a file-first cognitive model library MVP.
 You are not responsible for product strategy, marketing, sales, UI design, or broad feature invention.
 Product planning decisions come from the project owner and CCRA / ChatGPT-side architecture work.
 ## 2. Project Goal
 Build a minimal, file-first model library system that can represent cognitive models as:
 - Human-readable Markdown model cards
 - Machine-readable JSON model specs
 - Source article records
 - Source evidence excerpts
 - Regression test cases
 - Minimal model selector examples
 The current phase is `model_library_mvp`.
 The first sample models are:
 - QPI
 - Intellectual Archaeology
 ## 3. Core Principle
 Do not overbuild.
 The goal is not to create a full platform.
 The goal is to create a stable model asset foundation.
 Prefer:
 - JSON over database
 - Markdown over UI
 - Explicit schema over hidden convention
 - Simple scripts over complex services
 - Traceability over automation
 - Validation over feature expansion
 ## 4. Non-Goals
 Do not implement:
 - Full frontend application
 - Backend service
 - Database
 - Vector database
 - Full RAG system
 - User accounts
 - Authentication
 - Payment
 - Public platform
 - Multi-user collaboration
 - Complete knowledge graph
 - Automatic extraction from all articles
 - Full question-answering system
 If a task seems to require one of these, stop and ask for product confirmation.
 ## 5. Repository Layout
 Expected layout:
 ```text
 docs/
 schemas/
 models/
 cards/
 sources/
 tests/
 selector/
 scripts/
 reports/
 ```
 Each folder should contain a README explaining its purpose.
 Do not create a nested `model_library_mvp/` directory unless the project owner explicitly changes the repository strategy.
 ## 6. Data Rules
 Machine-readable files should use JSON.
 Human-readable model cards and documentation should use Markdown.
 Every model must eventually have:
 - `model_id`
 - `model_name`
 - `model_type`
 - `pipeline_position`
 - `one_sentence_definition`
 - `core_question`
 - `core_mechanism`
 - `source_articles`
 - `source_evidence`
 - `input_types`
 - `output_types`
 - `call_when`
 - `do_not_call_when`
 - `common_misuses`
 - `failure_modes`
 - `selection_priority`
 - `confidence_level`
 - `stability_profile`
 - `regression_status`
 - `productization_notes`
 ## 7. Source Traceability Rules
 Every model should reference source article IDs.
 Every model should reference source evidence excerpt IDs.
 Do not invent source IDs without adding matching records in `sources/source_articles.json` or `sources/source_excerpts.json`.
 If source content is not yet available, use placeholder records with clear notes such as:
 ```text
 raw_excerpt: "待填入原文片段"
 ```
 Do not pretend placeholder excerpts are verified evidence.
 ## 8. Regression Test Rules
 Every core model should have at least five regression cases:
 - Positive cases
 - Boundary cases
 - Misuse cases
 Regression tests should check whether the model is being used appropriately.
 They are not unit tests for code only. They are also product tests for cognitive model stability.
 ## 9. Selector Rules
 The minimal selector should not call an LLM in v0.1.
 It should use simple matching rules:
 - Trigger keywords
 - Input types
 - Negative triggers
 - Pipeline position
 - Selection priority
 The selector should output:
 - Recommended model IDs
 - Scores
 - Reasons
 - Routing notes
 ## 10. Coding Style
 Keep scripts simple and readable.
 Use Python only if scripts are needed.
 Avoid unnecessary dependencies.
 If using Python, prefer the standard library first.
 If a dependency is necessary, document it in README.
 ## 11. Validation Expectations
 Validation should eventually check:
 - JSON schema compliance
 - Unique model IDs
 - Valid source article references
 - Valid evidence excerpt references
 - Valid regression test model references
 - Required fields
 - Enum values
 Validation output should be written to:
 ```text
 reports/validation_report.md
 ```
 ## 12. Documentation Expectations
 When adding or changing structure, update relevant documentation.
 At minimum, keep these files consistent:
 - `README.md`
 - `AGENTS.md`
 - `docs/PROJECT_BRIEF.md`
 - `docs/DATA_CONTRACT.md`
 - `docs/WORKFLOW.md`
 - `docs/DECISIONS.md`
 ## 13. Decision Logging
 Any structural decision should be recorded in:
 ```text
 docs/DECISIONS.md
 ```
 Examples:
 - Why JSON is used instead of YAML
 - Why no database is used in v0.1
 - Why QPI and Intellectual Archaeology are the first sample models
 - Why selector is rule-based in v0.1
 - Why `model_library_mvp` is a phase name rather than a nested repository root
 ## 14. Definition of Done
 A task is done only when:
 - Files are created in the expected location
 - README or folder README is updated
 - JSON files are valid or clearly marked as draft
 - References between files are consistent
 - Validation status is documented
 - Non-goals have not been violated
 - Any open questions are listed in the handoff document
 ## 15. Handoff Requirement
 At the end of a work session, create or update:
 ```text
 docs/HANDOFF_TEMPLATE.md
 ```
 or a concrete handoff file such as:
 ```text
 reports/Codex_工程产物摘要_v0.1.md
 ```
 The handoff should include:
 - What was completed
 - What files changed
 - What assumptions were made
 - What does not yet work
 - What needs product judgment
 - Suggested next tasks
--- a/README.md
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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
 ```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.
 ```
 ## 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.
 ## 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.
--- a/cards/README.md
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 # Cards
 This folder will contain human-readable Markdown model cards.
 The first expected cards are:
 - `qpi.card.md`
 - `intellectual_archaeology.card.md`
 Model cards should explain model purpose, mechanism, usage boundaries, misuse risks, source traceability, and productization notes.
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 # Data Contract
 ## 1. Machine-Readable Format
 Use JSON for machine-readable data.
 Main JSON objects:
 - Model spec
 - Source article
 - Source excerpt
 - Regression case
 - Selector example
 ## 2. Human-Readable Format
 Use Markdown for:
 - Model cards
 - Project documentation
 - Extraction notes
 - Validation reports
 - Handoff reports
 ## 3. Model Spec Contract
 Every model JSON should include:
 - `model_id`
 - `model_name`
 - `model_type`
 - `pipeline_position`
 - `one_sentence_definition`
 - `core_question`
 - `core_mechanism`
 - `source_articles`
 - `source_evidence`
 - `input_types`
 - `output_types`
 - `call_when`
 - `do_not_call_when`
 - `common_misuses`
 - `failure_modes`
 - `selection_priority`
 - `confidence_level`
 - `stability_profile`
 - `regression_status`
 - `productization_notes`
 ## 4. Source Article Contract
 Every source article should include:
 - `source_id`
 - `title`
 - `source_type`
 - `related_models`
 - `source_status`
 Optional:
 - `author`
 - `date`
 - `file_path`
 - `notes`
 ## 5. Source Excerpt Contract
 Every source excerpt should include:
 - `excerpt_id`
 - `source_id`
 - `related_model_id`
 - `excerpt_type`
 - `summary`
 - `used_for`
 Optional:
 - `raw_excerpt`
 - `confidence`
 - `notes`
 ## 6. Regression Case Contract
 Every regression case should include:
 - `case_id`
 - `model_id`
 - `case_type`
 - `input`
 - `expected_behavior`
 - `failure_signal`
 Optional:
 - `expected_output_elements`
 - `notes`
 ## 7. Reference Integrity
 The following references must be valid:
 - `model.source_articles` -> `sources/source_articles.json`
 - `model.source_evidence` -> `sources/source_excerpts.json`
 - `regression_case.model_id` -> `models/*.model.json`
 - `source_excerpt.source_id` -> `sources/source_articles.json`
 - `source_excerpt.related_model_id` -> `models/*.model.json`
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 # Decision Log
 ## Decision 001: File-first architecture
 Status: Accepted
 Reason:
 The MVP should remain simple, local, transparent, and easy to inspect.
 A database is unnecessary before the model card schema and extraction protocol are stable.
 ## Decision 002: JSON for machine-readable model data
 Status: Accepted
 Reason:
 JSON is easy to validate with JSON Schema and suitable for later integration into scripts, selectors, or applications.
 ## Decision 003: Markdown for human-readable model cards
 Status: Accepted
 Reason:
 Markdown is easier for the project owner to read, edit, and review.
 ## Decision 004: QPI and Intellectual Archaeology as first sample models
 Status: Accepted
 Reason:
 QPI represents a routing model.
 Intellectual Archaeology represents a deep modeling model.
 Together they test two different kinds of model structures.
 ## Decision 005: Rule-based selector in v0.1
 Status: Accepted
 Reason:
 The first selector should validate data structure and model routing logic without relying on LLM calls.
 ## Decision 006: Use product root instead of a nested phase directory
 Status: Accepted
 Reason:
 `the-mindscape-of-bro-tsong` is the product and system boundary.
 `model_library_mvp` is the current phase and subsystem goal, not a separate root project.
 The repository should not start as `the-mindscape-of-bro-tsong/model_library_mvp/` because that would add unnecessary root-vs-subproject ambiguity before the product needs a monorepo layout.
--- a/docs/HANDOFF_TEMPLATE.md
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 # Codex Handoff Template
 ## 1. Current Work Session
 Date:
 Task:
 ## 2. Completed Work
 -
 ## 3. Files Created
 -
 ## 4. Files Modified
 -
 ## 5. Validation Status
 -
 ## 6. Assumptions Made
 -
 ## 7. Deviations From Plan
 -
 ## 8. Known Issues
 -
 ## 9. Questions for Product / CCRA
 -
 ## 10. Suggested Next Tasks
 1.
 2.
 3.
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 # Non-Goals
 The following are explicitly out of scope for v0.1.
 ## 1. Platform Features
 - User accounts
 - Authentication
 - Authorization
 - Payment
 - Public website
 - Admin dashboard
 - Multi-user collaboration
 ## 2. Knowledge Infrastructure
 - Full knowledge graph
 - Vector database
 - Large-scale RAG
 - Automatic article ingestion
 - Automatic model extraction from all articles
 ## 3. AI Workflow
 - Full multi-agent pipeline
 - LLM-based model selector
 - Complete question-answering system
 - Automated red-team review
 - Automated model stabilization
 ## 4. Content Scope
 - Managing all 100+ models
 - Importing all historical articles
 - Generating marketing content
 - Generating sales copy
 ## 5. UI Scope
 - Complex frontend
 - Visual graph editor
 - Drag-and-drop model editor
 - Dashboard analytics
--- a/docs/PROJECT_BRIEF.md
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 # Project Brief
 ## 1. Product Context
 This repository is the MVP foundation for The Mindscape of Bro Tsong.
 The current phase is the cognitive model management subsystem MVP, also called `model_library_mvp`.
 It supports a future problem-answering / cognitive-processing system that will use selected cognitive models to analyze user inputs.
 ## 2. First User
 The first user is the project owner.
 This is an OPC-oriented product workflow.
 The system should reduce the burden of managing, testing, and reusing cognitive models as a one-person company.
 ## 3. Core Need
 The project solves a model asset management problem:
 - Existing cognitive models are scattered across articles and previous model indexes.
 - Model cards need stronger source traceability.
 - Some early models require regression testing and stabilization.
 - The future question-answering system needs callable model specifications.
 ## 4. MVP Focus
 The MVP focuses on two models:
 - QPI
 - Intellectual Archaeology
 These two models are used to validate the model extraction protocol.
 ## 5. Long-Term Direction
 Future versions may support:
 - 8-10 core models
 - 20 extended models
 - Model selector
 - Multi-lens analysis workflow
 - Conflict summarization
 - Integrated question-answering system
 - Source article integration
 - Model regression dashboard
 These are not part of v0.1 unless explicitly requested.
 ## 6. Project Ecosystem
 This repository is separate from but related to:
 - `knowledge-vault`: upstream source archive and discussion records.
 - `ccpe-system`: expert-agent and runtime specification workspace.
 - `skills-vault`: canonical source for reusable automation skills.
 - `writing-workbench`: deep writing production workspace.
 - `video-workbench`: dimensional output workspace.
 This project may reference artifacts from those repositories, but its own boundary is the model asset foundation for The Mindscape of Bro Tsong.
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 # Workflow
 ## 1. Model Extraction Workflow
 The project follows this flow:
 ```text
 Original article / representative text
 -> source article record
 -> source evidence excerpts
 -> human-readable model card
 -> machine-readable model JSON
 -> regression cases
 -> selector examples
 -> validation report
 ```
 ## 2. Development Workflow
 For each task:
 1. Read `README.md` and `AGENTS.md`.
 2. Check `docs/PROJECT_BRIEF.md`.
 3. Modify the smallest necessary set of files.
 4. Keep JSON and Markdown versions consistent.
 5. Run or update validation.
 6. Update reports or handoff notes.
 7. Do not expand scope without confirmation.
 ## 3. Model Addition Workflow
 When adding a new model:
 1. Create a model JSON file in `models/`.
 2. Create a human-readable card in `cards/`.
 3. Add source article records.
 4. Add source evidence excerpts.
 5. Add regression cases.
 6. Add selector examples if relevant.
 7. Run validation.
 8. Update documentation.
 ## 4. Stabilization Workflow
 If a model is unstable:
 1. Mark `needs_stabilization: true`.
 2. Add risks in `stability_profile.main_risks`.
 3. Add boundary and misuse regression cases.
 4. Do not upgrade to stability level A until tests pass.
 ## 5. Handoff Workflow
 At the end of each work session:
 1. Summarize what changed.
 2. List created and modified files.
 3. Record validation status.
 4. Separate assumptions from verified facts.
 5. List questions that require product or CCRA judgment.
 6. Suggest the smallest useful next tasks.
--- a/docs/superpowers/plans/2026-06-16-project-initialization.md
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 # Project Initialization Implementation Plan
 > **For agentic workers:** REQUIRED SUB-SKILL: Use superpowers:subagent-driven-development (recommended) or superpowers:executing-plans to implement this plan task-by-task. Steps use checkbox (`- [ ]`) syntax for tracking.
 **Goal:** Initialize The Mindscape of Bro Tsong as a file-first cognitive model library MVP repository.
 **Architecture:** The repository root is the product boundary. `model_library_mvp` is recorded as the current phase rather than implemented as a nested directory. The first commit creates documentation, rules, directory purpose files, and a concrete handoff without implementing model extraction.
 **Tech Stack:** Markdown, JSON-ready folder structure, Git.
 ---
 ### Task 1: Create Root Documentation
 **Files:**
 - Create: `README.md`
 - Create: `AGENTS.md`
 - [x] **Step 1: Write project README**
 Create `README.md` with project definition, phase name, first sample models, non-goals, repository structure, validation expectations, and next steps.
 - [x] **Step 2: Write Codex working rules**
 Create `AGENTS.md` with role boundaries, non-goals, data rules, source traceability rules, regression expectations, selector expectations, validation expectations, and handoff requirements.
 ### Task 2: Create Rule Documents
 **Files:**
 - Create: `docs/PROJECT_BRIEF.md`
 - Create: `docs/DATA_CONTRACT.md`
 - Create: `docs/WORKFLOW.md`
 - Create: `docs/DECISIONS.md`
 - Create: `docs/NON_GOALS.md`
 - Create: `docs/HANDOFF_TEMPLATE.md`
 - [x] **Step 1: Create project brief**
 Document product context, first user, core need, MVP focus, long-term direction, and related project boundaries.
 - [x] **Step 2: Create data contract**
 Document JSON and Markdown responsibilities plus required fields for model specs, source articles, source excerpts, and regression cases.
 - [x] **Step 3: Create workflow rules**
 Document model extraction, development, model addition, stabilization, and handoff workflows.
 - [x] **Step 4: Create decision log**
 Record accepted structural decisions, including file-first architecture, JSON, Markdown, first sample models, rule-based selector, and flattened repository layout.
 - [x] **Step 5: Create non-goals and handoff template**
 Document v0.1 exclusions and a reusable handoff template.
 ### Task 3: Create Folder Purpose Files
 **Files:**
 - Create: `schemas/README.md`
 - Create: `models/README.md`
 - Create: `cards/README.md`
 - Create: `sources/README.md`
 - Create: `tests/README.md`
 - Create: `selector/README.md`
 - Create: `scripts/README.md`
 - Create: `reports/README.md`
 - [x] **Step 1: Create folder READMEs**
 Create one README per initial folder so Git tracks the intended structure without adding empty placeholder data files.
 ### Task 4: Create Session Handoff
 **Files:**
 - Create: `reports/Codex_工程产物摘要_v0.1.md`
 - [x] **Step 1: Write concrete session handoff**
 Record completed work, created files, validation status, assumptions, deviations, known issues, product questions, and suggested next tasks.
 ### Task 5: Publish Initialization
 **Files:**
 - Git metadata only
 - [ ] **Step 1: Initialize Git repository**
 Run: `git init`
 Expected: repository initialized in the current project root.
 - [ ] **Step 2: Set default branch to main**
 Run: `git branch -M main`
 Expected: current branch is `main`.
 - [ ] **Step 3: Add remote**
 Run: `git remote add origin https://git.wantsong.life/wantsong/the-mindscape-of-bro-tsong.git`
 Expected: `origin` points to the project remote.
 - [ ] **Step 4: Verify structure**
 Run: path checks for root files, docs files, and folder README files.
 Expected: all expected files exist.
 - [ ] **Step 5: Commit initialization**
 Run:
 ```text
 git add README.md AGENTS.md docs schemas models cards sources tests selector scripts reports
 git commit -m "chore: initialize model library mvp"
 ```
 Expected: a root commit containing the initialization files.
 - [ ] **Step 6: Tag initialization**
 Run: `git tag model-library-mvp-init-v0.1`
 Expected: local tag created on the initialization commit.
 - [ ] **Step 7: Push branch and tag**
 Run:
 ```text
 git push -u origin main
 git push origin model-library-mvp-init-v0.1
 ```
 Expected: branch and tag are available on the remote repository.
--- a/models/README.md
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 # Models
 This folder will contain machine-readable JSON model specifications.
 The first expected sample models are:
 - `qpi.model.json`
 - `intellectual_archaeology.model.json`
 Each model file must follow `docs/DATA_CONTRACT.md` and reference valid source and evidence records.
--- a/reports/Codex_工程产物摘要_v0.1.md
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 # Codex 工程产物摘要 v0.1
 ## 1. Current Work Session
 Date: 2026-06-16
 Task: Initialize The Mindscape of Bro Tsong repository for the `model_library_mvp` phase.
 ## 2. Completed Work
 - Initialized the project as a file-first cognitive model library MVP.
 - Kept `model_library_mvp` as the current phase name instead of creating a nested project directory.
 - Added root project documentation.
 - Added Codex working rules.
 - Added docs for project brief, data contract, workflow, decisions, non-goals, and handoff template.
 - Added purpose README files for all initial project folders.
 ## 3. Files Created
 - `README.md`
 - `AGENTS.md`
 - `docs/PROJECT_BRIEF.md`
 - `docs/DATA_CONTRACT.md`
 - `docs/WORKFLOW.md`
 - `docs/DECISIONS.md`
 - `docs/NON_GOALS.md`
 - `docs/HANDOFF_TEMPLATE.md`
 - `schemas/README.md`
 - `models/README.md`
 - `cards/README.md`
 - `sources/README.md`
 - `tests/README.md`
 - `selector/README.md`
 - `scripts/README.md`
 - `reports/README.md`
 - `reports/Codex_工程产物摘要_v0.1.md`
 ## 4. Files Modified
 - None. This was the initial file creation.
 ## 5. Validation Status
 - Directory structure created.
 - Markdown documentation created.
 - No schema, model JSON, selector config, or Python scripts have been implemented yet.
 - No runtime validation is available yet.
 ## 6. Assumptions Made
 - The repository root is `the-mindscape-of-bro-tsong`.
 - `model_library_mvp` is the current phase and subsystem goal, not a nested directory.
 - The first model extraction phase will focus on QPI and Intellectual Archaeology.
 - External source archives remain in `knowledge-vault`; this project stores selected model assets and source references needed for the product.
 ## 7. Deviations From Plan
 - The recommended nested `model_library_mvp/` path from the source initialization brief was intentionally flattened based on the project-root discussion.
 - Schema files and sample model JSON files were not created during initialization because the next phase will perform concrete model extraction.
 ## 8. Known Issues
 - JSON schemas do not exist yet.
 - QPI and Intellectual Archaeology model files do not exist yet.
 - Source article and source excerpt records do not exist yet.
 - Regression cases do not exist yet.
 - Selector rules do not exist yet.
 ## 9. Questions for Product / CCRA
 - Which source articles should be treated as canonical evidence for QPI?
 - Which source articles should be treated as canonical evidence for Intellectual Archaeology?
 - Should model IDs use English slugs only, or allow bilingual aliases in metadata?
 ## 10. Suggested Next Tasks
 1. Define JSON schemas for model specs, source articles, source excerpts, and regression cases.
 2. Extract the QPI model card and model JSON from canonical source material.
 3. Extract the Intellectual Archaeology model card and model JSON from canonical source material.
--- a/reports/README.md
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 # Reports
 This folder will contain generated or manually written project reports.
 Expected future files:
 - `validation_report.md`
 - `extraction_notes.md`
 - Concrete Codex handoff reports
 Reports should separate verified facts, assumptions, unresolved questions, and suggested next tasks.
--- a/schemas/README.md
+++ b/schemas/README.md
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 # Schemas
 This folder will contain JSON Schema files for machine-readable project data.
 Expected future files:
 - `model_card.schema.json`
 - `source_article.schema.json`
 - `source_excerpt.schema.json`
 - `regression_case.schema.json`
 Do not add schema complexity before the first two sample models are stable enough to validate.
--- a/scripts/README.md
+++ b/scripts/README.md
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 # Scripts
 This folder will contain simple local scripts for validation and selector demos.
 Expected future scripts:
 - `validate_models.py`
 - `validate_sources.py`
 - `validate_tests.py`
 - `run_selector_demo.py`
 Prefer Python standard library before adding dependencies.
--- a/selector/README.md
+++ b/selector/README.md
@ -0,0 +1,13 @@
 # Selector
 This folder will contain rule-based selector configuration and examples.
 The v0.1 selector should not call an LLM.
 It should use simple matching rules:
 - Trigger keywords
 - Input types
 - Negative triggers
 - Pipeline position
 - Selection priority
--- a/sources/README.md
+++ b/sources/README.md
@ -0,0 +1,10 @@
 # Sources
 This folder will contain source records and source evidence excerpts.
 Expected future files:
 - `source_articles.json`
 - `source_excerpts.json`
 Do not treat placeholder source records as verified evidence. Mark incomplete source material clearly.
--- a/tests/README.md
+++ b/tests/README.md
@ -0,0 +1,11 @@
 # Tests
 This folder will contain regression cases for cognitive model use.
 Regression cases are not only code tests. They are also product tests for whether a model is called appropriately.
 Each core model should eventually include:
 - Positive cases
 - Boundary cases
 - Misuse cases