Provenance-first extractive RAG: return verbatim source spans with citations using local ModernBERT or optional LLM-assisted extraction.

Reliable research infrastructure for AI agents. Evidence-backed web search with citations, confidence scores, and Clarity anti-hallucination. MCP server, REST API, Python SDK.

Deterministic policy language for AI agents. Z3 + TLA+ dual-engine formal verification. Runtime enforcement <1ms.

re!think it. System prompt teaching LLMs to execute two core tasks: complex answers without hallucinations, and creative ideas without clichés. Written in math-like logic, which LLMs parse better than plain language. Built for mid-to-high complexity tasks, featuring a Bypass branch to execute simple prompts directly without added cognitive overhead

Zero-hallucination reference verification for Claude Code — live CrossRef/S2/PubMed verification, verbatim abstract traceability, retraction check

Comprehensive guide to building production AI agent systems - Scale by Subtraction methodology

Stop hallucinations by verifying citations.

W.A.Y? (Who Are You? : I'm not a developer) — a personal AI harness that learns you, not a framework you learn

AI agent skill that creates formal, verifiable proofs of claims — every fact computed or cited, never asserted

Deterministic factual substrate for multi-agent AI. Shared evidence-backed facts and reproducible grounding through dataset_hash.

AI advisory board as a Claude Code skill + MCP server: verifies every quote word-for-word against public-domain sources, or abstains. Fail-closed fidelity.

TrustScoreEval: Trust Scores for AI/LLM Responses — Detect hallucinations, flags misinformation & Validate outputs. Build trustworthy AI.

Framework structures causes for AI hallucinations and provides countermeasures

A robust RAG backend featuring semantic chunking, embedding caching, and a similarity-gated retrieval pipeline. Uses GPT-4 and FAISS to provide verifiable, source-backed answers from PDFs, DOCX, and Markdown.

Track the source of every factual claim in AI agent output. Inline citations and source diversity scoring. Works with OpenClaw, Claude Code, Cursor, and any agent platform.

span is a CLI tool for AI agents that moves blocks text addressed by reference to save context and ensure faithful byte-level edits within a file or between multiple files.

Verification skills for academic research — grounds every claim in fetched evidence, not memory. Citation/figure/contradiction checking, arXiv monitoring, NRF grant writing.

DNA-Inspired LLM Veracity & Fidelity Framework — three-stage error correction (Polymerase, Exonuclease, MMR) modeled after DNA replication

Transform probabilistic LLMs into deterministic state machines to improve logic, prevent context loss, and generate unique, reliable responses.

Give Claude Code / Codex / any MCP agent real eyes and ears — closed-loop visual/audio/video verification with mandatory enforcement hooks, so agents stop reporting 'done' when it isn't.