A curated selection of core open-source engineering initiatives spanning empirical AI measurement, static audit intelligence, autonomous site remediation, agent infrastructure, and developer skill distribution.

Discovery & Measurement          Audit & Diagnostics           Remediation & Infrastructure
───────────────────────          ───────────────────           ────────────────────────────
     [GEO-Scope]           ──▶      [SAGE Audit]         ──▶          [SiteProbe]
(Empirical AI Visibility)        (SEO/AEO/GEO Audits)          (Autonomous Crawl & Patch)
                                                                            │
                                                                            ▼
                                                                     [Hamzad Gateway]
                                                               (Enterprise Agent OS Case Study)
                                                                            │
                                                                            ▼
                                                                  [Agent Skills Hub]
                                                             (Multi-Agent Skill Distribution)

Empirical AI Answer Visibility Measurement Framework

• Role: Observes, records, and quantifies entity mentions, recommendations, citations, and textual attributions across generative AI answer engines (Perplexity, Gemini Grounding) and parametric LLMs (GPT-4o, Claude).
• Core Technology: Python · Unicode Multi-Lingual Normalizer · Zero-Silent Fallback · Deterministic Replay · SHA-256 Verified Releases.
• Evidence Artifact: Evaluated across 45,000+ live observations in the Global AI Answers Benchmark 2026.2.

SEO / AEO / GEO Audit Intelligence Engine

• Role: Static diagnostic engine evaluating website crawlability, semantic extractability, JSON-LD Schema entity graphs, and citation survival proxies to understand and diagnose why sites fail to be cited by AI engines.
• Core Technology: Python · AST HTML Parser · 4-Layer Diagnostic Scoring · CLI & FastMCP Server.

Autonomous Website Crawling, Diagnostics & Code Remediation Platform

• Role: Crawls web applications, analyzes AI bot access policies (/llms.txt, robots.txt), and executes automated AST code and configuration patches with atomic rollback safeguards.
• Core Technology: Go · Python · Playwright Automation · MCP Remediation Tools.

Private AI Agent Infrastructure & Operating System (Architecture Case Study)

• Role: High-reliability enterprise AI gateway and agent execution runtime providing dynamic latency-based fallback routing, token optimization, and governance.
• Scope: Open architectural specifications, routing policies, and design patterns.

Distribution Layer for Reusable AI Agent Skills & MCP Tools

• Role: Standardized, production-tested skill catalog for AI coding agents (Claude Code, Cursor, OpenAI Codex, Antigravity).
• Scope: Unified skill schemas, MCP configuration templates, and workflow patterns.

Production-ready skills, workflow patterns, and token-optimized developer resources for autonomous coding agents.

Specialized engines, Laravel packages, and application backends powered by the AI Visibility Stack.

Governed, auditable, and local-first integration platforms connecting enterprise databases, ERPs, and industrial systems to AI Executive Intelligence without numeric hallucination or raw database exposure.

• Empirical Evidence Over Speculation: Every published metric is tied to verbatim, preserved API payloads (raw_responses.jsonl) verifiable offline.
• No Secret Algorithm Claims: We measure observable model outputs under documented prompts; we never claim to possess or reverse-engineer private AI ranking algorithms.
• Cryptographic Immutability: All benchmark releases include bit-level SHA-256 checksums to ensure zero data drift.
• Zero Silent Fallback: Live empirical runs strictly record errors rather than substituting mock or synthetic data.

Open for research initiatives, technical discussions, and architecture advisory in:

• Empirical AI Visibility Measurement: Benchmark protocol design, multi-provider observation pipelines, and citation analysis.
• GEO & AEO Research: Semantic extractability, JSON-LD entity graph structuring, and AI crawler accessibility.
• AI Systems Architecture: Enterprise AI gateways, dynamic model routing, and autonomous agent tooling.

Contact:

• Primary Website: molavi.pro

• Research Initiatives: molavi.pro/research

• ORCID: 0009-0009-6253-5354

• Direct Email: taqimolavi@gmail.com من در تقاطع بهینه‌سازی برای موتورهای هوش مصنوعی (GEO)، سئوی مبتنی بر هوش مصنوعی (AEO)، زیرساخت‌های ایجنت‌های نرم‌افزاری و سیستم‌های خودکار اصلاح کد فعالیت می‌کنم. تمامی ابزارها به صورت منبع‌باز و همراه با داده‌های تجربی و آزمون‌های قابل بازتولید منتشر شده‌اند:

• پایپ‌لاین دیده‌پذیری هوش مصنوعی: geo-scope (بنچ‌مارک تجربی)، answerpath-geo (کشف پرسش‌ها)، sage-audit (موتور ارزیابی ۳ لایه)، siteprobe (ربات اصلاح خودکار کد) و mcp-geo-server.

• هوش مصنوعی سازمانی و اتصال ERP: بستر متن‌باز iranian-enterprise-ai-bridge جهت اتصال امن و دترمینستیک نرم‌افزارهای سازمانی و کارخانجات به هوش مصنوعی مدیران ارشد با حفظ کامل حریم داده‌ها.

• زیرساخت ایجنت‌ها: مهارت‌های تخصصی ایجنت برای Claude Code، Cursor، Codex و Antigravity (شامل scholar-provenance جهت تبدیل پژوهش و کد به مقالات علمی معتبر، bale-bot-skills، n8n-agent-skills و mcp-agent-skills-hub).

• یادداشت‌ها و مقالات پژوهشی: در Molavi.pro فارسی در دسترس است.