# Monitor SEO Performance and Configure Alerts

SEO teams struggle to compare performance consistently and detect meaningful declines. This skill creates source-labeled reports and threshold-based alert plans from supplied or connected data.

## Install

```bash
npx skillstore add aaron-he-zhu/performance-monitor
```

## Metadata

- Status: approved
- Slug: aaron-he-zhu-performance-monitor
- Version: 17.0.0
- Author version: 17.0.0
- Skillstore revision: r1
- Version status: valid
- Tree hash: 1e762e298787c3a15a753075886d7b78f9fc0bfd12faa1759dbf38be5b9e254a
- 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/performance-monitor
- 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, env\_access
- Quality score: 78
- Quality tier: bronze
- Public page: https://skillstore.pages.dev/skills/aaron-he-zhu-performance-monitor
- Manifest: https://skillstore.pages.dev/api/skills/aaron-he-zhu-performance-monitor/manifest

## Capabilities

- Infers report or alert mode from the request and asks for clarification when intent is ambiguous.
- Compares current and prior SEO or GEO metrics while labeling each value by source.
- Produces audience-focused reports covering traffic, rankings, authority, backlinks, content, and AI visibility.
- Configures alert thresholds, priorities, delivery routes, cooldowns, maintenance windows, and escalation paths.
- Applies fixed readback windows and control comparisons to classify observed outcomes.
- Offers to save reusable monitoring summaries in a scoped memory directory.

## Use Cases

- Prepare Monthly Executive Reports: Compare current and prior SEO performance, summarize material changes, and assign prioritized actions with owners.
- Design Early Warning Alerts: Set baseline-aware alerts for traffic, ranking, technical, backlink, competitor, and AI citation changes.
- Build Client Performance Reviews: Create audience-specific dashboards with source labels, missing-data notes, recommendations, and next-period goals.

## Prompt Templates

### Create a Basic Monthly Snapshot

```
Create an executive SEO report for [domain], comparing the last 30 days with the prior 30 days. Mark unavailable metrics clearly.
```

### Configure Traffic and Ranking Alerts

```
Configure traffic and ranking alerts for [domain] using my baseline data. Include thresholds, priorities, channels, cooldowns, and response plans.
```

### Review Search and AI Visibility

```
Compare AI citations and search KPIs for [domain] across [periods]. Separate observed changes, plausible explanations, missing evidence, and recommended actions.
```

### Evaluate a Controlled Readback

```
Evaluate [change] against [control] over [readback window]. Classify the result as Promote, Keep-testing, Rollback, or Unproven, with caveats and next-readback date.
```

## Limitations

- It cannot fetch current metrics unless compatible tools are connected or the user supplies data.
- It reports existing CITE and CORE-EEAT scores but does not calculate them.
- Reliable reports and alerts require comparison periods, baselines, or clearly labeled estimates.
- It proposes alert configurations but does not schedule or send notifications without external automation.

## Best Practices

- Provide current and comparison-period data with source names and freshness dates.
- Use measured baselines and normal volatility when setting thresholds.
- Separate observed changes from explanations, recommendations, and follow-up investigations.

## Anti Patterns

- Do not present estimated metrics as measured values.
- Do not configure alert categories that the user did not request.
- Do not claim causation from a simple before-and-after comparison.

## Security Audit

- Audited at: 2026-07-12T13:27:49.209\+00:00
- Summary: Most detections are Markdown syntax, documentation links, or metadata URLs without executable behavior. SKILL.md line 63 directs agents to run a Python ledger command with a domain argument. This creates command execution and input-handling risk, but no malicious or exfiltration intent was found.

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- Downloads: 6
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- Popularity score: 0