--- artifact: A name: Diagnostic Record layer: 1-2 client: "" audit_id: "" date: "" prompt_library_version: "" engine_set_version: "" competitor_set_version: "" status: draft | qa | approved qa: evidence_tier_gate: pending | pass | fail banned_language_gate: pending | pass | fail human_review_gate: pending | pass | fail --- # Artifact A — Diagnostic Record Purpose: Pure observation. Zero recommendations. This document must never reach a client raw — it is internal evidentiary backing behind the synthesized client report. 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. 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. Gate field scope: | Field type | Gate applies? | Reason | |---|---:|---| | Executive summary, observation narrative, competitor observation summaries | Yes | Authored interpretation | | Raw prompt text, raw engine output, source titles/URLs, platform field labels, quoted business names | No | Observed evidence or system metadata | --- ## 1. Scope and Method - Client: - Audit ID: - Date: - Prompt library version: - Engine set version: - Competitor set version: - Prompt count: - Engine count: - Competitor set: ### Method notes Describe the sampling method, engine set, and limitations. (Not gated — this is methodology, not a finding.) ### Limitations > "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." --- ## 2. Run Inventory | Run ID | Prompt ID | Engine | Timestamp | Raw output stored | Screenshot stored | |---|---|---|---|---|---| | | | | | | | --- ## 3. Core Visibility Index (quantitative, 70 pts) Directly countable from captured audit runs only. No qualitative bands folded in. | Component | Weight | Score | |---|---:|---:| | Mention rate | 35 | | | Mention strength / position | 20 | | | Description accuracy | 15 | | | Total | 70 | | ## 4. Directional Context Indicators (Tier 2, reported separately — not part of the 70) | Indicator | Purpose | Evidence tier | |---|---|---| | Source/citation quality | Whether supporting sources favor client, competitor, or neither | Tier 2 | | Competitor observation share | Relative appearance frequency across tested prompts | Tier 2 | | Engine variance | Inconsistency across engines (see per-engine sourcing note, §6) | Tier 2 | 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."* --- ## 5. Prompt-Level Observation Ledger | Prompt ID | Prompt text | Engine | Timestamp | Client observed | Mention strength | Accuracy state | Competitors observed | Source observations | Evidence tier | |---|---|---|---|---|---|---|---|---|---| | | | | | | | | | | | --- ## 6. Competitor Observation Summary | Competitor | Observed count | Strong mentions | Moderate mentions | Weak mentions | Source observations | Notes | |---|---:|---:|---:|---:|---|---| | | | | | | | | Per-engine sourcing context (Tier 2, indicative — source: Ty business-readiness review, 2026-08-06; requires direct audit observation or authoritative documentation to upgrade): | Engine | Primary local-answer source, working model | Highest-leverage signal, working model | Evidence tier | |---|---|---|---| | Gemini | Google's local graph | GBP, Maps/Places, reviews, categories, hours | Tier 2 | | ChatGPT | Bing web index + partner place data + open web | Foursquare places data, Bing-visible consistency, business website, directory NAP | Tier 2 | | Claude | Tools/APIs + web, often Google Places when looking up locals | Google Places/Maps-aligned data, clear website, consistent public facts | Tier 2 | Do not score identical prompts across engines as if testing the same underlying signal — they source differently. --- ## 7. Feed-Forward This file's findings do not get restated in a duplicate entity/evidence format. They feed forward directly into: - `docs/clients//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. - `docs/clients//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. 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. --- ## 8. QA Reference - Evidence tier gate: - Banned language gate (authored fields only): - Human review gate: - Reviewer: - Review date: - Transcribed into data-inventory-v1.md: - Transcribed into threat-register-v1.md: - Linked to Layer 1b owner-access record (if applicable):