Rev 5: Add Section 13 Corpus of States for Trustworthy AI Discovery and Interaction (after protocol research, cross-referenced to avoid duplication)

docs/product-idea-review.md

@@ -1,6 +1,6 @@
 # Product Idea Review: Digital Operations Partner
 
-**Date**: 2026-07-24 (Rev 1) / 2026-07-25 (Rev 2–3) / 2026-07-25 (Rev 4)  
+**Date**: 2026-07-24 (Rev 1) / 2026-07-25 (Rev 2–4) / 2026-07-25 (Rev 5)  
 **Status**: Phase 1 – Business Definition  
 **Reviewer context**: External strategic review based on current repository documentation and extended concept exploration.
 
@@ -10,6 +10,8 @@
 
 **Revision 4 notes**: Added corrected Model Context Protocol (MCP) research analysis under Technical Research, including Shopify Storefront MCP reality and the gap between live MCP servers and transparent major-LLM usage.
 
+**Revision 5 notes**: Added Section 13 — Corpus of States for Trustworthy AI Discovery and Interaction — placed after protocol research. Cross-references §4 (listing surfaces) and §12 (protocols) so the corpus is a unifying inventory, not a restatement.
+
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 ## 1. Executive Summary
@@ -334,7 +336,75 @@ In short, non-adoption leaves both the service and its clients on the informatio
 
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+## 13. Corpus of States for Trustworthy AI Discovery and Interaction (Rev 5)
+
+A local business that wants AI systems to discover it accurately and interact with it reliably must produce and continuously maintain a set of digital states. These states fall into three layers: **Discoverability**, **Understanding**, and **Actionability**. Missing or inconsistent states in any layer create silent customer loss.
+
+This section is the unifying inventory. Detailed listing surfaces are defined in **§4**; protocol mechanics (A2A, MCP) and their adoption timelines are in **§12**. The corpus does not restate those lists — it organizes the *states a business must keep current* so AI systems can find, model, and act on the entity.
+
+### 13.1 Layer 1 — Discoverability States
+*Where AI systems and agents first find the business*
+
+The primary existence surfaces are those already prioritized in §4 (Google Business Profile, Apple Business Connect / Apple Maps, Bing Places, Yelp, and key citations), plus NAP consistency across them and a crawlable website. These are the “existence” states. If they are missing, conflicting, or stale, the business is hard to find or is found incorrectly.
+
+### 13.2 Layer 2 — Understanding States
+*How AI systems form a correct model of what the business is and does*
+
+| State | What it is | Why it matters | Maintenance burden |
+|-------|------------|----------------|---------------------|
+| **Clear service / product definitions** | Explicit descriptions of what is offered (and what is not) | Prevents hallucinated services and wrong recommendations | High |
+| **Structured data (schema.org)** | LocalBusiness, Service, FAQPage, OpeningHours, etc. | Machine-readable facts that reduce ambiguity | Medium |
+| **FAQ corpus** | Natural-language answers to common questions | Primary training and retrieval material for AI systems | High |
+| **llms.txt** | Emerging machine-readable guidance file for AI crawlers | Signals preferred interpretation and allowed use | Low–Medium |
+| **sitemap.xml + robots.txt** | Crawl guidance | Controls what is discoverable and how | Low |
+| **Consistent entity signals** | Same business name, categories, service list across site + listings | Reinforces a single coherent model | Ongoing |
+| **Current hours, service area, contact methods** | Operational facts | Directly affects whether an AI routes a customer correctly | High (time-sensitive) |
+
+These are the “meaning” states. Weak or contradictory understanding states cause AI systems to misrepresent the business even when they can find it.
+
+### 13.3 Layer 3 — Actionability States
+*How AI systems and agents can take the next step with the business*
+
+| State | What it is | Why it matters | Maintenance burden | Maturity |
+|-------|------------|----------------|---------------------|----------|
+| **Booking / scheduling endpoint** | Cal.com, Calendly, or equivalent that supports real availability | Allows agents to move from recommendation to appointment | Medium | Live today via MCP (see §12.2) |
+| **MCP server / tool endpoint** | Standardized interface for agents to query or act | Enables tool use without custom integration | Medium–High | Live for platforms; not yet transparently used by major consumer LLMs (§12.2) |
+| **Agent Card (A2A)** | Published description of agent capabilities and endpoint | Allows other agents to discover and call the business’s agent | Medium (future) | Early / emerging (§12.1) |
+| **Commerce surfaces (UCP-compatible)** | Product catalog, cart, checkout exposed in agentic form | Required for agents to complete purchases | High (mostly product businesses) | Emerging |
+| **Real-time availability / status** | Live inventory, open slots, job status | Prevents agents from promising what cannot be delivered | High | Varies by system |
+
+These are the “interaction” states. Without them the business remains informational only; agents can talk about it but cannot complete useful work with it. Protocol detail and non-adoption risk for MCP and A2A remain in §12.
+
+### 13.4 Cross-Cutting Trust States
+
+Across all three layers, several states determine whether AI systems treat the business as trustworthy:
+
+- **Freshness** — How recently key facts (hours, services, phone, availability) were verified.
+- **Consistency** — Agreement across website, listings (§4), schema, and any agent endpoints.
+- **Evidence quality** — Preference for Verified over Indicative signals (aligned with the project’s evidence model).
+- **Permission / robots / llms.txt posture** — Clear signals about what AI systems are allowed to do with the content.
+- **Human oversight loop** — Ability to detect drift and correct it before it propagates into AI recommendations.
+
+### 13.5 Practical Priority Order for Most Local Service SMBs
+
+1. Correct and complete Google Business Profile (highest leverage discovery + understanding; §4–5)
+2. Consistent NAP + core facts across Apple, Bing, Yelp, and website
+3. Clear service definitions + FAQ corpus on the website
+4. Basic structured data (LocalBusiness, Service, FAQPage, hours)
+5. Working booking path (preferably MCP-enabled such as Cal.com; §12.2)
+6. llms.txt + clean crawl configuration
+7. Later: Agent Card / A2A readiness and any relevant commerce (UCP) surfaces (§12.1)
+
+### 13.6 Implication for Digital Operations Partner
+
+Trustworthy AI discovery and interaction is not a single file or a single listing. It is a **maintained corpus of states** spanning existence surfaces (listings), meaning surfaces (website content, schema, FAQs, entity consistency), and action surfaces (booking, MCP, future Agent Cards).
+
+Digital Operations Partner’s core value is helping SMBs produce, monitor, and keep these states accurate and aligned — so that when an AI system or agent looks at the business, it sees one coherent, current, and actionable entity rather than a fragmented or outdated set of signals. The public Business Assessment AI (§6.2) diagnoses the current state of this corpus; ongoing monitoring and approved correction keep it current; protocol readiness (§12) extends the action layer as standards mature.
+
+---
+
 *Rev 1 synthesized repository documentation and concept exploration on 2026-07-24.  
 Rev 2 incorporates multi-surface expansion, AI-mediated GTM, public Business Assessment AI, tiered packaging, and current delegated-access feasibility (2026-07-25).  
 Rev 3 adds Technical Research section with structured A2A protocol analysis (2026-07-25).  
-Rev 4 adds corrected MCP protocol research analysis, including Shopify Storefront MCP and the transparent-usage gap (2026-07-25).*
+Rev 4 adds corrected MCP protocol research analysis, including Shopify Storefront MCP and the transparent-usage gap (2026-07-25).  
+Rev 5 adds Section 13 Corpus of States for Trustworthy AI Discovery and Interaction, placed after protocol research and cross-referenced to §4 and §12 (2026-07-25).*