Skills offsite-signal-analyzer
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offsite-signal-analyzer

v17.0.0 Content revision r1 Safe 🌐 Network accessβš™οΈ External commandsπŸ“ Filesystem access

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.

Supports: Claude Codex Code(CC)
πŸ₯‰ 79 Bronze

Install with my Agent

Copy this request to your Agent. It includes the canonical Skill page and manifest.

Agent request
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.

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

Safe
v7 β€’ 7/12/2026 Open versioned report

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.

4
Files scanned
525
Lines analyzed
3
Review items
0
False positives ignored
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.

Medium
Ruby/shell backtick execution
**Keyless unlinked-mention read (backlinks mode)**: `python3 "${CLAUDE_PLUGIN_ROOT}/scripts/connecto
The line explicitly directs execution of Python connector and ledger commands. Brand and domain placeholders may become user-controlled shell values without defined validation.
Medium
Ruby/shell backtick execution
**Keyless upstream AI-citation spot-check (ai-referrals mode)**: referral logs only show clicks *aft
The line directs execution of Tavily and ledger Python commands using query and domain placeholders. Unsafe interpolation could permit command injection.
Medium
Ruby/shell backtick execution
**Zero-dependency measurement loop (ai-referrals)**: store each period's AI-channel KPIs and let the
The line instructs execution of ledger.py with domain and data placeholders. An unquoted domain in a shell command creates a plausible injection path.
Audited by: codex View Audit History β†’
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Open versioned report
Security Assessment

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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/7

BibTeX 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: Medium
45
Architecture
100
Maintainability
87
Content
65
Community
100
Spec Compliance

What 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

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.

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?
Provide a backlink or referring-domain export, anchor data, and optional competitor domains. Without this data, the skill cannot calculate link metrics.
What data does AI referrals mode require?
Provide a GA4 source and medium export, Search Console data, server logs, or a connected analytics source.
Which AI assistants can it identify?
The starter pattern includes ChatGPT, Perplexity, Copilot, Gemini, Claude, DeepSeek, Doubao, Qwen, Poe, and related domains.
Can it upload a disavow file?
No. It can prepare candidates and guidance, but a person should review and upload the final file.
Does AI referral traffic prove a citation?
No. It shows that an AI answer linked to the site, but it does not prove citation position or prominence.
Can it analyze both modes together?
It keeps both datasets separate. When a request includes both, select one mode first and run the other afterward.

Developer Details

License

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