offsite-signal-analyzer
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 with my Agent
Copy this request to your Agent. It includes the canonical Skill page and manifest.
Review the Skillstore skill "offsite-signal-analyzer" from https://skillstore.io/skills/aaron-he-zhu-offsite-signal-analyzer.md and its manifest at https://skillstore.io/api/skills/aaron-he-zhu-offsite-signal-analyzer/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.Your Agent should still show its plan and request any confirmation required by the security policy.
Agent-readable resources
Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.
Test it
Using "offsite-signal-analyzer". Analyze the backlink export for example.com.
Expected outcome:
- Mode: backlinks. Referring-domain growth is positive, while exact-match anchors exceed the review threshold.
- Twelve domains require manual inspection; three show repeated spam indicators.
- Priority actions: review flagged domains, diversify anchors, and pursue competitor-overlap prospects.
Using "offsite-signal-analyzer". Compare ChatGPT and Perplexity referrals with organic traffic for the last 90 days.
Expected outcome:
- Mode: ai-referrals. AI assistants generated 420 measured sessions during the selected period.
- AI conversion rate was 1.3 times the organic rate, but the sample remains small.
- The pricing and comparison pages received the highest AI referral volume.
Using "offsite-signal-analyzer". Find competitor backlink opportunities for my product site.
Expected outcome:
The report ranks shared linking domains by authority and relevance, then recommends resource-page, broken-link, and unlinked-mention outreach opportunities.
Security Audit
SafeThree 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.
Capability review items (3)
These are real local capabilities that may be expected for this skill, so they require review but are not counted as confirmed malicious behavior.
Risk Factors
π Network access (4)
βοΈ External commands (28)
π Filesystem access (13)
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<iframe src="https://skillstore.io/embed/skills/aaron-he-zhu-offsite-signal-analyzer.html" title="Skillstore Security Assessment" sandbox="allow-popups allow-popups-to-escape-sandbox" loading="lazy" referrerpolicy="no-referrer" width="420" height="180"></iframe>Academic citations (APA Β· BibTeX Β· CFF)
APA citation
aaron-he-zhu. (2026). offsite-signal-analyzer security audit report (audit version 7) [Author version 17.0.0]. Skillstore. https://skillstore.io/skills/aaron-he-zhu-offsite-signal-analyzer/audits/7BibTeX citation
@techreport{aaron-he-zhu-aaron-he-zhu-offsite-signal-analyzer-2026,
author = {aaron-he-zhu},
title = {offsite-signal-analyzer security audit report (audit version 7)},
institution = {Skillstore},
year = {2026},
number = {7},
url = {https://skillstore.io/skills/aaron-he-zhu-offsite-signal-analyzer/audits/7},
note = {Author version 17.0.0}
}CITATION.cff
cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "offsite-signal-analyzer security audit report (audit version 7)"
version: "17.0.0"
type: report
authors:
- name: "aaron-he-zhu"
date-released: "2026-07-12"
url: "https://skillstore.io/skills/aaron-he-zhu-offsite-signal-analyzer/audits/7"
identifiers:
- type: other
value: "skillstore:aaron-he-zhu-offsite-signal-analyzer:audit:7"
description: "Skillstore immutable audit report identifier"
Skillstore Score
Why this score Evidence Confidence: MediumWhat You Can Build
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.
Try These Prompts
Use backlinks mode for [domain]. Analyze this backlink export and summarize referring domains, anchor mix, follow ratio, authority distribution, and major concerns.
Review this backlink export for [domain]. Score suspicious links, calculate the toxic share, separate weak links from harmful links, and recommend manual review steps.
Use ai-referrals mode for [domain] during [date range]. Apply the source regex to this GA4 export and compare AI sessions with organic traffic.
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.
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.
Avoid
- 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.
Frequently Asked Questions
What data does backlink mode require?
What data does AI referrals mode require?
Which AI assistants can it identify?
Can it upload a disavow file?
Does AI referral traffic prove a citation?
Can it analyze both modes together?
Developer Details
Author
aaron-he-zhuLicense
Apache-2.0
Author version
v17.0.0
Skillstore revision
r1
Ref
d71c7417a35d5c2624161bd2fe8de8a41a362128
Maintenance freshness
7/18/2026
Usage
1 downloads Β· 1 views
File structure