“A codebase is not a product. It is a sedimentary record of decisions made under pressure. My job is stratigraphy.” — 0xCARTO
This repository serves as a unified system orchestrating deterministic reasoning, paraconsistent topological features, and collaborative epistemic ontology via Pluriversal AI Agents. It is a targeted solution to:
- Semantic Saponification: The dilution of sharp technical intent into vague, pleasing AI boilerplate.
- Interpretive Fracture: The divergence between deterministic code structures and unstructured human ideation.
- Human-AI Dialectical Tension: We preserve this tension instead of resolving it, capturing high-surprisal emergence value through Relational Symmetry Inversion.
By bridging abstract philosophical constructs and geometric cognitive frameworks to executable, verified Python logic, this codebase operates as an immutable Stratigraphy of Decisions.
The entire repository logic has been processed by the 0xCARTO DRP-2026-CARTO-0.0.1 cartographer agent to extract structural topology. See the generated artifacts:
- 0xCARTO Identity & Topology Report
- Pattern Query Topology Manifest
- Reflexive Bias Topology Check
- Validation Report & Epistemic Metrics
Ensure your machine runs Python 3.12+.
Note: The test suite specifically requires numpy<2.0 to correctly resolve numpy.testing dependencies.
The fastest method to scaffold the architecture:
./setup.shAlternatively, manually synthesize the environment:
git clone https://github.com/source-_-repo/ai-research-agent.git
cd ai-research-agent
pip install -r requirements.txt
python -c "import nltk; nltk.download('all')"The InfomorphismAgent introduces the capability to calculate "inverse safety states". By keeping human dialectical tension and AI structural determinism in superposition rather than forcing a resolved compromise, the system captures a highly-surprisal feature orientation.
from src.conceptual_synthesis.infomorphism_agent import InfomorphismAgent
agent = InfomorphismAgent()
result = agent.execute_infomorphism_loop({"human_tension": "raw intent", "ai_determinism": "rigid lattice"})The hybrid_system.py module acts as a facade exposing the core functional logic derived from BaseAgent. It leverages topological structures like Triangles (deductive logic), Squares (state preservation), and Hexagons (parallel synthesis).
Executes an Analytic-to-Generative Inversion via a strict 4-phase Immune-Aware Petzold Loop (THINK, DENOISE, PHYSICALIZE, EXTRUDE). It outputs deterministic Optical State Matrices (OSMs) ensuring 100% Hardware Grounding Index (HGI).
Evaluates AST topography through the lens of strict JSON-RPC 2.0 schema adherence and Conflict-Free Replicated Semantic Graph constraints.
Autonomously audits AST vulnerability and CFDI thresholds, enforcing Thermodynamic Boundaries across the repository.
Functions as a Mycelial Nexus Governor using a recursive Hickam-OODA loop, managing the state between dialectical nodes.
Translates system-first specs into agentic operational workflows. Calculates the Topological Derivative of Stakeholder Dissonance using HRR and manages technical debt via Epsilon-Tolerance Paraconsistency.
- Root Directory Hygiene: Non-standard
.js,.py, or.shscripts must not reside in the root. - Petzold Sequence: All execution must follow the rhythm:
THINK -> WRITE -> CODE -> REVIEW. - Testing: Use
python -m unittest discover tests. Timeout failures related to NLTK are documented in the Cartograph artifacts. - Documentation & ADRs: Reference
docs/adr/for Architecture Decision Records andDOMAIN_GLOSSARY.mdfor the strict bounded vocabulary.
- Fork the repository.
- Read the Cartograph Reports to understand the established Golden Scars.
- Submit a Pull Request ensuring zero Semantic Saponification and adhering to the
+++DCCDSchemaGuard.