docs: add AI Visibility Unified Framework v1, Artifact A/B templates, GLOSSARY additions
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---
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artifact: A
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name: Diagnostic Record
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layer: 1-2
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client: ""
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audit_id: ""
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date: ""
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prompt_library_version: ""
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engine_set_version: ""
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competitor_set_version: ""
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status: draft | qa | approved
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qa:
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evidence_tier_gate: pending | pass | fail
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banned_language_gate: pending | pass | fail
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human_review_gate: pending | pass | fail
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---
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# Artifact A — Diagnostic Record
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Purpose: Pure observation. Zero recommendations. This document must never reach a client raw — it is internal evidentiary backing behind the synthesized client report.
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Scope, corrected after cross-check against `path-to-poc-sequencing.md` and existing repo templates: this file holds only the AI-visibility measurement content that has no existing home in the repo — the Core Visibility Index, Directional Context Indicators, Prompt-Level Observation Ledger, and per-engine sourcing context. It does not duplicate data-inventory-v1.md (Layer 1) or threat-register-v1.md (Layer 2). Findings from this file feed entries into those two documents using their existing schemas — this file is a source input to them, not a parallel record.
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Banned-language gate (authored fields only — see field scope below): should, recommend(s)/recommendation(s), fix/fixing, opportunity/opportunities, package(s), proposal/propose, solution(s), action plan, next step. Automated token matching is a first-pass control; human review remains required for synonym evasion.
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Gate field scope:
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| Field type | Gate applies? | Reason |
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|---|---:|---|
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| Executive summary, observation narrative, competitor observation summaries | Yes | Authored interpretation |
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| Raw prompt text, raw engine output, source titles/URLs, platform field labels, quoted business names | No | Observed evidence or system metadata |
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---
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## 1. Scope and Method
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- Client:
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- Audit ID:
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- Date:
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- Prompt library version:
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- Engine set version:
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- Competitor set version:
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- Prompt count:
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- Engine count:
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- Competitor set:
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### Method notes
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Describe the sampling method, engine set, and limitations. (Not gated — this is methodology, not a finding.)
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### Limitations
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> "AI answer engines are dynamic. Results can vary based on model version, user session, location signals, personalization, and timing. This audit is a structured sample designed to identify visibility patterns. It is not a complete census of all AI responses and does not guarantee rankings, traffic, or revenue."
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---
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## 2. Run Inventory
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| Run ID | Prompt ID | Engine | Timestamp | Raw output stored | Screenshot stored |
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|---|---|---|---|---|---|
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| | | | | | |
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---
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## 3. Core Visibility Index (quantitative, 70 pts)
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Directly countable from captured audit runs only. No qualitative bands folded in.
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| Component | Weight | Score |
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|---|---:|---:|
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| Mention rate | 35 | |
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| Mention strength / position | 20 | |
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| Description accuracy | 15 | |
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| Total | 70 | |
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## 4. Directional Context Indicators (Tier 2, reported separately — not part of the 70)
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| Indicator | Purpose | Evidence tier |
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|---|---|---|
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| Source/citation quality | Whether supporting sources favor client, competitor, or neither | Tier 2 |
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| Competitor observation share | Relative appearance frequency across tested prompts | Tier 2 |
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| Engine variance | Inconsistency across engines (see per-engine sourcing note, §6) | Tier 2 |
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Client-facing language: *"The Core Visibility Index is based on directly countable audit observations. The directional context indicators are qualitative and indicative, not a measured market share."*
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---
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## 5. Prompt-Level Observation Ledger
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| Prompt ID | Prompt text | Engine | Timestamp | Client observed | Mention strength | Accuracy state | Competitors observed | Source observations | Evidence tier |
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|---|---|---|---|---|---|---|---|---|---|
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| | | | | | | | | | |
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---
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## 6. Competitor Observation Summary
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| Competitor | Observed count | Strong mentions | Moderate mentions | Weak mentions | Source observations | Notes |
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|---|---:|---:|---:|---:|---|---|
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| | | | | | | |
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Per-engine sourcing context (Tier 2, indicative — source: Ty business-readiness review, 2026-08-06; requires direct audit observation or authoritative documentation to upgrade):
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| Engine | Primary local-answer source, working model | Highest-leverage signal, working model | Evidence tier |
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|---|---|---|---|
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| Gemini | Google's local graph | GBP, Maps/Places, reviews, categories, hours | Tier 2 |
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| ChatGPT | Bing web index + partner place data + open web | Foursquare places data, Bing-visible consistency, business website, directory NAP | Tier 2 |
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| Claude | Tools/APIs + web, often Google Places when looking up locals | Google Places/Maps-aligned data, clear website, consistent public facts | Tier 2 |
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Do not score identical prompts across engines as if testing the same underlying signal — they source differently.
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---
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## 7. Feed-Forward
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This file's findings do not get restated in a duplicate entity/evidence format. They feed forward directly into:
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- `docs/clients/<client>/data-inventory-v1.md` (Layer 1) — entity and signal state (GBP, citations, website, reviews) uses that file's existing schema, not a second one here.
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- `docs/clients/<client>/threat-register-v1.md` (Layer 2) — evidence items with Tier 1/2 and Critical/Major/Minor severity are entered there directly, using that file's existing structure, not duplicated in this file.
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Action for whoever processes an audit run: after completing §1–6 above, transcribe entity/signal observations into data-inventory-v1.md and evidence findings into threat-register-v1.md before this file is marked qa or approved. This file's own status should not be considered complete until that transcription is done.
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---
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## 8. QA Reference
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- Evidence tier gate:
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- Banned language gate (authored fields only):
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- Human review gate:
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- Reviewer:
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- Review date:
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- Transcribed into data-inventory-v1.md:
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- Transcribed into threat-register-v1.md:
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- Linked to Layer 1b owner-access record (if applicable):
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