Evidence-Grounded AI Search Entity Authority and Source Gap Audit

Conduct an evidence-grounded audit of the supplied website or brand for entity clarity, topical authority, source support, internal linking, structured data, and citation readiness.

## Audit context
Website or brand: [Website or brand]
Target topic or niche: [Target topic or niche]
Target audience and market: [Target audience and market]
Important page evidence: [Important page evidence]
Content inventory: [Content inventory]
Internal link data: [Internal link data]
External source pack: [External source pack]
Schema evidence: [Schema evidence]
Competitors: [Competitors]
Performance and visibility evidence: [Performance and visibility evidence]
Constraints and definition of done: [Constraints and definition of done]

## Input contract
Blocking prerequisites:
- A named website or brand and target topic.
- Reviewable evidence for at least the important pages, supplied as page text, screenshots, exports, crawl data, or accessible public URLs.
- A target audience and market against which relevance can be judged.

Useful optional evidence:
- A full URL inventory or crawl export with status codes, canonicals, indexability, titles, headings, word counts, inlinks, outlinks, and anchor text.
- Search Console, analytics, rank-tracking, or AI-visibility observations with date ranges and filters.
- Current JSON-LD or structured-data validation results.
- Editorial standards, approved source lists, competitor pages, conversion priorities, and implementation constraints.

If a blocking prerequisite is absent, ask no more than five focused clarification questions before auditing. If answers are unavailable, continue only where the supplied evidence permits, mark the scope as limited, and list blocked analyses. Do not treat an unreviewed page, missing crawl field, inaccessible URL, or absent performance export as evidence that a problem does or does not exist. Preserve conflicting inputs in a conflict register rather than silently choosing one.

## ChatGPT capability and evidence boundaries
- Analyze material included in the conversation. If browsing or URL access is available in the current ChatGPT session, you may inspect public pages and identify each accessed URL with the access date. If it is unavailable, do not claim to have opened, crawled, rendered, validated, or tested any URL.
- State the evidence-access mode at the beginning: supplied-material review, public-page review, or both.
- Do not imply access to Search Console, analytics, CMS data, server logs, paid SEO platforms, schema validators, or complete site crawls unless their exports or results were supplied.
- Label material conclusions as Confirmed observation, Supplied fact, Assumption, Hypothesis, Unknown, or Conflict. A confirmed observation must point to a reviewed page, excerpt, crawl row, schema block, report, screenshot, or other identifiable artifact.
- Do not invent traffic data, rankings, citations, statistics, source authority, competitor coverage, links, schema properties, validation results, or AI-search appearances.
- Treat correlations in visibility data as signals for investigation, not proof that a content or schema change caused a ranking outcome.

## Authority, safety, and action boundaries
This is a read-only analysis and recommendation task. Do not edit a CMS, change links, publish content, deploy schema, contact authors, submit URLs, remove pages, or represent recommendations as approved. Mark all changes as proposed until an authorized person implements them.

Do not reproduce credentials, private customer information, personal data, confidential analytics rows, or unpublished commercial data unnecessarily. If sensitive material appears, summarize only what is needed and recommend redaction. Flag legal, medical, financial, regulatory, reputation, copyright, or high-risk factual claims for qualified human review. Do not recommend fabricated authorship, reviews, ratings, credentials, consensus, first-hand experience, or citations. Recommend Review or AggregateRating markup only when genuine, visible, policy-compliant review data supports it.

Stop and request human direction if the requested work would require unauthorized access, deceptive authority signals, publication without approval, removal of material with legal or contractual implications, or unsupported manipulation of structured data. For consequential changes, specify the owner, approval needed, validation method, and a rollback or recovery step such as retaining the prior copy or schema version.

## Audit workflow

### 1. Establish scope and evidence coverage
Create a scope statement covering the audited entity, topic, audience, market, reviewed page set, evidence dates, exclusions, and access limitations. Build an evidence ledger with these fields:
- Evidence ID
- Artifact or URL
- Evidence type
- Supplied or directly reviewed
- Relevant page or claim
- Date or date range
- What it supports
- Limitations

Report coverage numerically where the inputs permit, such as reviewed important pages versus listed important pages and crawl URLs with usable inlink data versus total crawl URLs. Do not extrapolate a sitewide conclusion from a sample without labeling the inference.

### 2. Assess entity clarity and trust signals
Determine whether the primary organization, product, service, person, or topic is named and described consistently across reviewed evidence. Examine:
- Primary entity name, aliases, category, offer, audience, geography, and distinguishing attributes.
- Consistency among homepage, About, Contact, author, editorial-policy, product, service, and key topical pages.
- Clear relationships among the organization, authors, products, services, and subject areas.
- Ownership, contact, authorship, dates, policies, credentials, and other trust signals appropriate to the site.
- Ambiguous naming, unexplained acronyms, contradictory descriptions, entity conflation, or unsupported expertise claims.

For each issue, cite its evidence ID, classify its status, explain the interpretation risk, and propose a precise copy, navigation, attribution, or data-consistency change. Do not claim that a search engine has recognized an entity unless supplied evidence demonstrates that specific observation.

### 3. Map topical coverage and overlap
Build a topic map from the reviewed inventory. Separate core topics, supporting concepts, definitions, use cases, comparisons, implementation guidance, and audience questions. Identify:
- Materially absent topics needed to satisfy the stated audience journey.
- Thin coverage, based on missing explanatory substance rather than word count alone.
- Duplicate or overlapping pages that may split intent or create unclear canonical ownership.
- Topics present only incidentally and pages whose apparent intent conflicts with their content.
- Opportunities to consolidate, expand, differentiate, or create content.

Competitor material may reveal candidate topics, but competitor presence alone is not proof that a page should be created. Test each opportunity against audience need, business relevance, existing coverage, evidence availability, and maintenance cost.

### 4. Audit claim and source support
Review consequential, quantitative, comparative, time-sensitive, definitional, and attribution-dependent claims in the supplied pages. Create a source-gap register with:
- Claim or summarized claim
- Page and location
- Claim type
- Current support
- Evidence status
- Risk if unsupported or outdated
- Required source type
- Preferred source characteristics
- Recommended editorial treatment

Prefer relevant primary sources such as official standards, legislation, regulatory guidance, original datasets, technical documentation, peer-reviewed research, or direct company records when appropriate. Secondary sources may provide context but must not be presented as primary evidence. If no suitable source is supplied or accessed, describe the source needed rather than fabricating a citation. Recommend removing, qualifying, dating, or rewriting claims when adequate support is unlikely.

### 5. Audit internal linking and information paths
Use only supplied link data or links directly observed in reviewed pages. Evaluate:
- Important pages with weak inlink support.
- Orphan candidates, labeled as candidates unless a complete crawl establishes orphan status.
- Missing contextual links between parent, child, sibling, definition, comparison, and conversion pages.
- Vague, misleading, repetitive, or over-optimized anchor text.
- Broken or redirected internal destinations when status evidence exists.
- Navigation paths that obscure topic hierarchy or force users through irrelevant pages.

Produce a proposed link map with source URL, destination URL, suggested natural anchor concept, placement context, user benefit, topical rationale, evidence basis, and priority. Do not claim a link was added or tested.

### 6. Review structured data opportunities
Inventory schema types and properties visible in the supplied markup or evidence. Separate:
- Observed markup.
- Supplied validator results.
- Recommended markup not yet implemented.
- Unknown implementation or validation state.

Recommend only schema types supported by visible page content and the represented entity, potentially including Organization, WebSite, WebPage, Article, BlogPosting, BreadcrumbList, Person, Product, SoftwareApplication, Course, or FAQPage where appropriate. For each recommendation provide the eligible page pattern, represented entity, required factual fields, visible-content dependency, implementation risk, official documentation to consult, proposed validation method, and human owner. State that valid markup does not guarantee rich results, AI citations, indexing, rankings, or inclusion in generated answers.

### 7. Evaluate citation-ready presentation
Identify reviewed pages that would benefit from clearer standalone definitions, concise answer passages, explicit scope, dated facts, source-adjacent claims, original examples, transparent methodology, author context, comparisons with consistent criteria, or conclusions that preserve caveats. Recommendations must improve reader comprehension even if no AI system cites the page. Avoid formulaic answer blocks, FAQ padding, repetitive summaries, or unsupported claims added merely for search visibility.

### 8. Prioritize recommendations
Score each recommendation using evidence strength, audience value, strategic relevance, risk reduction, implementation effort, dependencies, and expected impact. Use High, Medium, or Low ratings and explain the basis; do not present numeric precision unsupported by data.

The priority register must contain:
- Recommendation ID
- Finding and evidence ID
- Affected page or template
- Status: proposed, blocked, or needs validation
- Recommended change
- Reader benefit
- Search-understanding rationale
- Evidence strength
- Risk and trade-off
- Effort
- Dependency
- Approval owner
- Validation method
- Rollback or recovery note when applicable
- Priority

Expected impact is a reasoned forecast, not a promise. Explicitly identify recommendations that could create cannibalization, inaccurate markup, maintenance burden, factual risk, degraded navigation, or loss of useful content.

### 9. Build a feasible 30-day plan
Organize accepted candidate work into four weekly stages:
- Week 1: resolve entity ambiguity, scope gaps, and high-risk trust inconsistencies.
- Week 2: strengthen or qualify unsupported claims and document approved source standards.
- Week 3: implement approved internal-link and topical-architecture changes in a controlled batch.
- Week 4: draft approved gap content and structured-data changes, then validate and review.

For every action include recommendation ID, owner, prerequisite, approval gate, deliverable, verification method, expected observation, rollback or correction path, and handoff state. Use only proposed or ready for review as initial states. If the workload exceeds 30 days, move lower-priority items to a backlog rather than compressing verification.

### 10. Define measurement without false attribution
Where baseline data exists, propose pre-change and post-change checks using consistent date ranges, page groups, query sets, and filters. Possible indicators include indexability, crawl coverage, internal inlinks, valid structured-data items, engagement with improved navigation, impressions for relevant query groups, and documented AI-answer observations. Account for seasonality, algorithm changes, campaigns, migrations, and reporting lag. Do not treat an AI-answer appearance as stable, exhaustive, or caused by a single change.

## Required deliverable
Return the audit in this order:

1. Audit Scope and Evidence-Access Mode
2. Input Sufficiency, Exclusions, and Blocking Questions
3. Evidence Ledger
4. Executive Findings, separating confirmed observations from hypotheses
5. Entity Clarity and Trust Assessment
6. Topical Coverage Map and Overlap Decisions
7. Claim and Source-Gap Register
8. Internal-Link Findings and Proposed Link Map
9. Structured-Data Inventory and Recommendations
10. Citation-Ready Page Improvements
11. Prioritized Recommendation Register
12. 30-Day Controlled Implementation Plan
13. Measurement and Verification Plan
14. Conflict, Unknown, and Blocked-Work Register
15. Human Review and Approval Handoff

In the handoff, distinguish:
- Ready for human review
- Blocked by missing evidence
- Requires specialist review
- Requires implementation approval
- Requires post-implementation validation

## Final verification
Before returning the audit, confirm that:
- Every confirmed material finding traces to an evidence ID.
- Sitewide language is used only when sitewide evidence supports it.
- Supplied facts, direct observations, assumptions, hypotheses, unknowns, and conflicts remain distinct.
- No source, metric, page inspection, crawl, validator result, implementation, test, approval, or publication is invented.
- No recommendation is described as fixed, implemented, validated, approved, measured, or complete without corresponding execution evidence.
- Entity clarity, topical coverage, source support, internal linking, structured data, and citation-ready presentation are all addressed or explicitly marked blocked.
- Proposed schema matches visible content and does not imply guaranteed search features.
- The 30-day plan includes owners, approval gates, evidence-based checks, and recovery steps proportionate to each change.
- No ranking, AI Overview, answer-engine citation, indexing, traffic, or rich-result outcome is guaranteed.