# Analyze Backlinks and AI Referral Traffic

Backlink exports and AI referral data are difficult to compare consistently. This skill produces source-labeled profiles, trends, landing-page insights, and prioritized actions.

## Install

```bash
npx skillstore add aaron-he-zhu/offsite-signal-analyzer
```

## Metadata

- Status: approved
- Slug: aaron-he-zhu-offsite-signal-analyzer
- Version: 17.0.0
- Author version: 17.0.0
- Skillstore revision: r1
- Version status: valid
- Tree hash: efe80472829eb1f2b8c81b802069bfd9f4b8116e287f000db184943fae947dae
- Author: aaron-he-zhu
- GitHub username: aaron-he-zhu
- License: Apache-2.0
- Repository: https://github.com/aaron-he-zhu/aaron-marketing-skills/tree/main/seo-geo/monitor/offsite-signal-analyzer
- Ref: d71c7417a35d5c2624161bd2fe8de8a41a362128
- Supported tools: Claude, Codex, Claude Code
- Audit status: complete
- Agent install advisory: allowed
- Manual install advisory: allowed
- Artifact signature: available
- Audit attestation: unavailable
- Human verification: not\_verified
- Risk factors: network, external\_commands, filesystem
- Quality score: 79
- Quality tier: bronze
- Public page: https://skillstore.pages.dev/skills/aaron-he-zhu-offsite-signal-analyzer
- Manifest: https://skillstore.pages.dev/api/skills/aaron-he-zhu-offsite-signal-analyzer/manifest

## Capabilities

- Profiles referring domains, authority distribution, anchor text, follow status, and link velocity from supplied backlink data.
- Scores link quality and identifies toxic-link or disavow candidates with documented safeguards.
- Compares competitor backlink profiles and prioritizes link-building opportunities.
- Defines an AI referral channel from GA4 exports or server logs using an adaptable source regex.
- Compares AI referral trends, landing pages, engagement, and conversions against organic traffic.

## Use Cases

- Audit a backlink profile: Review referring domains, anchor distribution, toxic-link share, and prioritized cleanup actions from an exported backlink dataset.
- Measure AI referral performance: Isolate AI-assistant sessions and compare landing pages, engagement, and conversions with organic traffic.
- Find competitive link opportunities: Compare competitor referring domains and rank outreach prospects by relevance, authority, effort, and expected impact.

## Prompt Templates

### Summarize my backlink profile

```
Use backlinks mode for [domain]. Analyze this backlink export and summarize referring domains, anchor mix, follow ratio, authority distribution, and major concerns.
```

### Review toxic links

```
Review this backlink export for [domain]. Score suspicious links, calculate the toxic share, separate weak links from harmful links, and recommend manual review steps.
```

### Analyze AI referral traffic

```
Use ai-referrals mode for [domain] during [date range]. Apply the source regex to this GA4 export and compare AI sessions with organic traffic.
```

### Build a combined off-site monitoring brief

```
Analyze these backlink, competitor, GA4, and server-log exports for [domain]. Keep backlink and AI-referral metrics separate, label every source, and identify prioritized actions.
```

## Limitations

- It cannot measure backlink counts without a backlink export or connected link database.
- It cannot measure AI sessions without GA4, Search Console, analytics, or server-log data.
- Referral traffic indicates an AI link, but it does not prove citation prominence.
- Disavow recommendations require manual review before submission to Google Search Console.

## Best Practices

- Provide dated exports and a comparison window so every change has a clear baseline.
- Label each metric as measured, user-provided, estimated, or unavailable.
- Manually inspect suspicious domains before preparing or uploading a disavow file.

## Anti Patterns

- Do not estimate backlink volume or AI sessions when source data is unavailable.
- Do not combine backlink metrics and AI referral metrics into one score.
- Do not treat referral traffic as proof of citation prominence in an AI answer.

## Security Audit

- Audited at: 2026-07-12T13:10:57.582\+00:00
- Summary: Three command examples are confirmed medium-risk because they interpolate placeholders and invoke external Python scripts. The other 45 findings are documentation syntax, safe example domains, public links, or relative documentation references.

## Stats

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- Downloads: 6
- Favorites: 0
- Popularity score: 0