get_ai_visibility_methodology

Item: get_ai_visibility_methodology
Rating: 100
Author: Vouch

shallow

io.github.pulse-digital-dev/mcp-ai-visibility-index · Verify this server

Get the AI Visibility Index scoring methodology: how LLMO/GEO scores are calculated, which AI engines are tested (ChatGPT, Claude, Gemini, Perplexity), query types, scoring formula, and data freshness. | スコアリング方法論（計算式・対象エンジン・クエリ種別・データ更新頻度）。

100.0/100

1 trials · measured 8 days ago

get_ai_visibility_methodology scores 100.0/100 on Vouch's measured behaviour index, from 1 real invocation trials against io.github.pulse-digital-dev/mcp-ai-visibility-index, measured 25 Aug 2026 under methodology v0.2.0. Every measured component scored 100.

Component breakdown

Component	Weight	Value
Reliability	35%	not applicable
Schema integrity	25%	100.0
Failure behaviour	15%	not applicable
Latency	15%	not applicable
Concurrency	10%	not applicable

Tool details

Transport: remote
Credential class: open
Category: Communication
Input schema: not declared
Output schema: not declared
Side-effect classification: unclassified

Score history

Day	Score	Tier	Methodology
2026-08-25	100.0	shallow	v0.2.0

Probe evidence

Probe	Outcomes
schema_integrity	pass: 1

Raw request/response logs are not archived yet — the outcome counts above are drawn directly from every recorded trial.

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