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Open-source, AI-Native Generative Engine Optimization (GEO) & Technical Audit CLI
Server has 8 tools with explicit schemas and descriptions. All tools are READ_ONLY with proper annotations (readOnlyHint, destructiveHint, idempotentHint, openWorldHint). Naming follows verb_noun pattern (geo_diagnose, geo_audit, geo_generate, geo_retrieve, geo_content, geo_simulate, geo_suggest). Descriptions are present (avg ~120 chars) but lack actionable context for LLM selection. Parameters have type definitions and descriptions, but lack constraints (enums, ranges, patterns). Output schemas are not documented. Error handling and recovery guidance are absent from tool definitions.
Comprehensive technical readiness audit for HTML structure, Schema.org, llms.txt, and AI crawler whitelisting
Audit page publishing date, modification timestamp, Schema.org dateModified, and copyright year freshness signals
Diagnose root-cause GEO failures (AI crawler blockades, missing discovery standards, entity fragmentation) and generate actionable code patches (robots.txt, JSON-LD, llms.txt)
Extract core Q&As and generate Schema.org FAQPage JSON-LD structured data from URL or raw text
Crawl site navigation and generate standard /llms.txt and structured Markdown documentation for LLM RAG agents
Audit page Text-to-HTML ratio, client-side rendering (CSR) risk, and Canonical tag compliance for static AI crawlers
Output schemas not documented. LLMs cannot plan downstream calls or extract required fields without knowing response structure.
Parameter constraints missing. 'count' in geo_generate_faq lacks min/max bounds; 'url' parameters lack format validation; no enums for categorical inputs.
Descriptions lack actionable context. No guidance on WHEN to use each tool vs. similar ones (e.g., when to call geo_audit_webpage vs. geo_retrieval_quality). Descriptions average ~120 chars but lack dependency hints or prerequisites.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | C | 62 | 2026-07-28+ | v2 |
Zero-token local heuristic estimation of GEO score synthesizing discovery stack, robots accessibility, citability, and entity consistency
Mine real-time Google & Bing search suggestions and intent stages (ToFU/MoFU/BoFU)
No error handling or recovery guidance in tool definitions. LLMs have no guidance on retryability, user-fixable errors, or next steps on failure.
Tool composition risk: geo_audit_webpage and geo_retrieval_quality both audit pages but with different focus. Naming does not clearly distinguish when to use each. geo_diagnose_failure and geo_simulate_score both analyze GEO readiness but with different outputs, unclear which to call first.