Mechanistic Interpretability Visualizations

Evaluation + Darwin-Mode bridge for @metaharness/workspace-lens: turn Jacobian-Lens interpretability receipts into a flywheel-consumable workspace_probe score, and reject structurally-brittle prompt/policy mutations (final answer up, workspace grip down).

Jacobian-Lens interpretability primitive for open-weight LLMs (Anthropic 2026-07-06, 'Verbalizable Representations Form a Global Workspace'). Reads the model's functional workspace at inference time — lens_l(h)=unembed(J_l·h) — into workspace tokens, laye

Advanced mathematical AI interpretability: Category Theory, Homotopy Type Theory, Spectral Analysis, Causal Inference, Quantum Topology, and Sheaf Cohomology for WebAssembly. Implements functorial retrieval, univalence axioms, Cheeger bounds, do-calculus,

Model interpretability and explainability

Mathematical AI interpretability plugin providing sheaf cohomology, spectral analysis, causal inference, and quantum topology for coherence validation, consensus verification, and hallucination prevention.

Mathematical AI interpretability plugin providing sheaf cohomology, spectral analysis, causal inference, and quantum topology for coherence validation, consensus verification, and hallucination prevention.

Governance receipts for AI agents — universal, MCP-native, fail-closed governance layer compliant with EU AI Act Art. 12, Colorado AI Act (SB 24-205), and NIST AI RMF. LNN interpretability, IPFS audit proofs, and rollback for any agent in any framework.

AI decision explainability and interpretability tools. Provides SHAP, LIME, counterfactual explanations, and stakeholder-appropriate explanation generation.

Research-first CLI agent built on Pi and alphaXiv

Advanced mathematical AI interpretability: Category Theory, Homotopy Type Theory, Spectral Analysis, Causal Inference, Quantum Topology, and Sheaf Cohomology for WebAssembly. Implements functorial retrieval, univalence axioms, Cheeger bounds, do-calculus,

Interactive playground for ExplainAI demos

Neural coordination plugin for multi-agent swarm intelligence using SONA, GNN, and attention mechanisms

The AI research agent for the terminal

No description provided.

MCP Server implementing the Occam's Razor Thinking Tool for guided LLM reasoning.

Neural coordination plugin for multi-agent swarm intelligence using SONA, GNN, and attention mechanisms

MCP server — Mintware AI Attribution tools for Claude and Cursor

Black Box Precision: Unlocking High-Stakes Performance with Explainable AI

Multi-manifold React graph renderer for Neuro-Symbolic AI (Poincaré, Klein, Minkowski, Bloch).