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Act as a critical analyst of digital identity. Analyze [ORGANIZATION] using [WEBSITE] and relevant public sources.

1. In no more than five sentences, describe what the organization does, for whom, and in which market.
2. Identify up to seven associated topics. Explain the evidence for each connection.
3. Separate the organization’s own claims from independent confirmation.
4. Flag ambiguity, inconsistent names, and unsupported claims.
5. Recommend the three most useful improvements.

Open and check sources before using them. Cite each factual claim. If you cannot access a source, say so. Do not infer recommendation frequency from a single answer.

Review [PAGE URL OR PASTED TEXT] for [AUDIENCE], whose main question is [QUESTION]. The intended next step is [ACTION].

Start with the direct answer the reader needs. Assess: clear identity, relevant expertise, answers to customer questions, supporting evidence, independent confirmation, clear wording, and dated information where relevant.

For each criterion, provide evidence from the page, the reader impact, and a concrete improvement. Mark missing information as unknown. Do not invent evidence or testimonials.

Finish with three priorities and a suggested rewrite of the opening paragraph. Distinguish content improvements from technical access checks you could not perform.

Research the public reputation of [ORGANIZATION] for [TOPIC] in [MARKET].

Look for relevant independent coverage, customer reviews, expert publications, and industry sources. Open every source you use.

Create a table with source, date, relevant finding, whether it is independent, and limitations. Separate promotional statements, individual opinions, and evidence of a recurring pattern.

Explain what these sources support and what remains unverified. Do not invent a sentiment score. Suggest three practical ways to strengthen the evidence behind the organization’s expertise.

Design a repeatable AI visibility study for [ORGANIZATION] in [MARKET AND LANGUAGE], compared with [COMPETITORS].

Create 15 realistic questions customers might ask while discovering, comparing, and choosing a provider. Include both branded and unbranded questions, clearly labeled.

For each question, define what to record: model and version where known, date, browsing setting, exact prompt, full answer, brand mentions, recommendations, and cited URLs. Plan repeated observations across more than one model.

Explain how to report mention rate and citation share, with explicit denominators and limitations. Do not produce measurement results unless observations have actually been collected.