# Track Search Rankings and SERP Visibility

Ranking changes are hard to interpret without consistent baselines and source labels. This skill compares snapshots, identifies meaningful movements, and recommends focused SEO actions.

## Install

```bash
npx skillstore add aaron-he-zhu/rank-tracker
```

## Metadata

- Status: approved
- Slug: aaron-he-zhu-rank-tracker
- Version: 17.0.0
- Author version: 17.0.0
- Skillstore revision: r1
- Version status: valid
- Tree hash: fef62a1e81daccfa8419c27e9c419ab3461b6f85ae6a57b37df6f2e1e07db915
- 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/rank-tracker
- 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: external\_commands, network, filesystem
- Quality score: 77
- Quality tier: bronze
- Public page: https://skillstore.pages.dev/skills/aaron-he-zhu-rank-tracker
- Manifest: https://skillstore.pages.dev/api/skills/aaron-he-zhu-rank-tracker/manifest

## Capabilities

- Configures tracking by domain, keyword, market, device, language, frequency, priority, and competitor.
- Compares current keyword positions with a prior baseline and labels each delta.
- Identifies gains, declines, new rankings, lost rankings, and stable terms.
- Tracks featured snippets, People Also Ask, media packs, local packs, and AI Overview citations.
- Compares competitor positions, visibility share, and keyword-level threats.
- Produces ranking summaries with source labels, likely causes, and recommended actions.

## Use Cases

- Review Weekly Keyword Movement: Compare weekly exports, identify important gains and losses, and prioritize investigation.
- Monitor Competitive Search Visibility: Compare priority terms against direct competitors and highlight emerging threats or opportunities.
- Summarize Portfolio Ranking Health: Create a sourced ranking summary across markets, devices, SERP features, and AI citations.

## Prompt Templates

### Create a Baseline

```
Track rankings for [domain] using [keywords] in [market] on [device]. Label every position by source and create the first baseline.
```

### Compare Two Snapshots

```
Compare these ranking snapshots for [domain]. Show each keyword delta, biggest gains, biggest losses, new rankings, lost rankings, and next actions.
```

### Analyze SERP and AI Visibility

```
Analyze SERP features and AI visibility for [keywords]. Compare ownership, citations, competitors, content gaps, and source confidence. Mark unavailable metrics clearly.
```

### Diagnose a Ranking Decline

```
Investigate this ranking decline using [snapshots], [competitor data], and [technical signals]. Separate measured facts from hypotheses and prioritize recovery actions by urgency.
```

## Limitations

- It needs user-provided data or connected tools for measured rankings.
- It cannot confirm ranking causes from position changes alone.
- Missing SERP features or AI citation data are reported as unavailable.
- A first run creates a baseline and cannot report historical movement.

## Best Practices

- Provide dated snapshots with the same market, device, language, and search engine.
- Separate measured values, user-provided values, estimates, and unavailable metrics.
- Review large movements against competitors, technical events, and known algorithm updates.

## Anti Patterns

- Do not claim movement when no prior baseline exists.
- Do not present inferred positions or causes as measured facts.
- Do not compare snapshots with different markets or devices without clear segmentation.

## Security Audit

- Audited at: 2026-07-12T13:41:55.063\+00:00
- Summary: One medium-risk command invocation is confirmed because it directs execution of an external Python script with an unquoted domain placeholder. The other findings are false positives caused by Markdown syntax, metadata URLs, relative documentation links, and ordinary prose.

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