clay-observability
Monitor Clay enrichment pipeline health, credit consumption, and data quality metrics. Use when setting up dashboards for Clay operations, configuring alerts for credit burn, or tracking enrichment success rates. Trigger with phrases like "clay monitoring", "clay metrics", "clay observability", "monitor clay", "clay alerts", "clay dashboard", "clay credit tracking".
Best use case
clay-observability is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Monitor Clay enrichment pipeline health, credit consumption, and data quality metrics. Use when setting up dashboards for Clay operations, configuring alerts for credit burn, or tracking enrichment success rates. Trigger with phrases like "clay monitoring", "clay metrics", "clay observability", "monitor clay", "clay alerts", "clay dashboard", "clay credit tracking".
Teams using clay-observability should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/clay-observability/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How clay-observability Compares
| Feature / Agent | clay-observability | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Monitor Clay enrichment pipeline health, credit consumption, and data quality metrics. Use when setting up dashboards for Clay operations, configuring alerts for credit burn, or tracking enrichment success rates. Trigger with phrases like "clay monitoring", "clay metrics", "clay observability", "monitor clay", "clay alerts", "clay dashboard", "clay credit tracking".
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Clay Observability
## Overview
Monitor Clay data enrichment pipeline health across four dimensions: credit consumption velocity, enrichment success rates (hit rates), data quality scores, and CRM sync reliability. Clay's credit-based pricing model makes observability essential for cost control.
## Prerequisites
- Clay account with table access
- Metrics infrastructure (Prometheus/Grafana, Datadog, or custom)
- Webhook receiver that logs enrichment results
- Understanding of your enrichment column configuration
## Instructions
### Step 1: Instrument Your Clay Webhook Handler
```typescript
// src/clay/metrics.ts — collect metrics from enriched data flowing back from Clay
interface ClayMetrics {
enrichmentsReceived: number;
enrichmentsWithEmail: number;
enrichmentsWithCompany: number;
enrichmentsWithPhone: number;
estimatedCreditsUsed: number;
averageICPScore: number;
leadsTier: { A: number; B: number; C: number; D: number };
}
class ClayMetricsCollector {
private metrics: ClayMetrics = {
enrichmentsReceived: 0,
enrichmentsWithEmail: 0,
enrichmentsWithCompany: 0,
enrichmentsWithPhone: 0,
estimatedCreditsUsed: 0,
averageICPScore: 0,
leadsTier: { A: 0, B: 0, C: 0, D: 0 },
};
private scoreSum = 0;
record(lead: Record<string, any>, creditsPerRow: number = 6) {
this.metrics.enrichmentsReceived++;
if (lead.work_email) this.metrics.enrichmentsWithEmail++;
if (lead.company_name) this.metrics.enrichmentsWithCompany++;
if (lead.phone_number) this.metrics.enrichmentsWithPhone++;
this.metrics.estimatedCreditsUsed += creditsPerRow;
const score = lead.icp_score || 0;
this.scoreSum += score;
this.metrics.averageICPScore = this.scoreSum / this.metrics.enrichmentsReceived;
if (score >= 80) this.metrics.leadsTier.A++;
else if (score >= 60) this.metrics.leadsTier.B++;
else if (score >= 40) this.metrics.leadsTier.C++;
else this.metrics.leadsTier.D++;
}
getReport(): string {
const m = this.metrics;
const emailRate = m.enrichmentsReceived > 0
? ((m.enrichmentsWithEmail / m.enrichmentsReceived) * 100).toFixed(1)
: '0';
const companyRate = m.enrichmentsReceived > 0
? ((m.enrichmentsWithCompany / m.enrichmentsReceived) * 100).toFixed(1)
: '0';
return [
`=== Clay Enrichment Report ===`,
`Total processed: ${m.enrichmentsReceived}`,
`Email find rate: ${emailRate}%`,
`Company match rate: ${companyRate}%`,
`Avg ICP score: ${m.averageICPScore.toFixed(1)}`,
`Lead distribution: A=${m.leadsTier.A} B=${m.leadsTier.B} C=${m.leadsTier.C} D=${m.leadsTier.D}`,
`Estimated credits used: ${m.estimatedCreditsUsed}`,
`Cost per email found: ${(m.estimatedCreditsUsed / Math.max(m.enrichmentsWithEmail, 1)).toFixed(1)} credits`,
].join('\n');
}
}
```
### Step 2: Set Up Prometheus Metrics (Optional)
```typescript
// src/clay/prometheus-metrics.ts
import { Counter, Gauge, Histogram } from 'prom-client';
// Counters
const clayEnrichmentsTotal = new Counter({
name: 'clay_enrichments_total',
help: 'Total enrichments received from Clay',
labelNames: ['table', 'status'],
});
const clayCreditsUsed = new Counter({
name: 'clay_credits_used_total',
help: 'Estimated Clay credits consumed',
labelNames: ['table', 'enrichment_type'],
});
// Gauges
const clayHitRate = new Gauge({
name: 'clay_enrichment_hit_rate',
help: 'Enrichment hit rate percentage',
labelNames: ['table', 'field'],
});
const clayCreditBalance = new Gauge({
name: 'clay_credit_balance',
help: 'Remaining Clay credits',
});
const clayICPScore = new Histogram({
name: 'clay_icp_score',
help: 'Distribution of ICP scores',
buckets: [20, 40, 60, 80, 100],
labelNames: ['table'],
});
// Record enrichment
function recordEnrichment(table: string, lead: Record<string, any>) {
clayEnrichmentsTotal.inc({ table, status: lead.work_email ? 'enriched' : 'empty' });
clayCreditsUsed.inc({ table, enrichment_type: 'waterfall' }, 6);
clayICPScore.observe({ table }, lead.icp_score || 0);
}
```
### Step 3: Configure Alerting Rules
```yaml
# prometheus/clay-alerts.yml
groups:
- name: clay-enrichment
rules:
- alert: ClayCreditBurnHigh
expr: rate(clay_credits_used_total[1h]) > 200
for: 15m
labels:
severity: warning
annotations:
summary: "Clay credit burn rate > 200/hour. Monthly projection: {{ $value | humanize }} credits"
- alert: ClayLowEmailHitRate
expr: clay_enrichment_hit_rate{field="email"} < 40
for: 30m
labels:
severity: warning
annotations:
summary: "Email find rate below 40% on table {{ $labels.table }}. Check input data quality."
- alert: ClayCreditBalanceLow
expr: clay_credit_balance < 500
labels:
severity: critical
annotations:
summary: "Clay credit balance below 500. Enrichments will stop when credits run out."
- alert: ClayWebhookFailureRate
expr: rate(clay_enrichments_total{status="error"}[15m]) > 0.1
labels:
severity: warning
annotations:
summary: "Clay webhook callback failure rate > 10%"
```
### Step 4: Build a Dashboard
Key panels for a Clay observability dashboard:
```yaml
dashboard_panels:
row_1:
- name: "Credit Balance"
type: gauge
metric: clay_credit_balance
thresholds: [500, 1000, 5000]
- name: "Credits Used Today"
type: stat
metric: increase(clay_credits_used_total[24h])
- name: "Email Hit Rate"
type: gauge
metric: clay_enrichment_hit_rate{field="email"}
thresholds: [40, 60, 80]
row_2:
- name: "Credit Burn Rate (hourly)"
type: timeseries
metric: rate(clay_credits_used_total[1h])
- name: "ICP Score Distribution"
type: histogram
metric: clay_icp_score
row_3:
- name: "Lead Tier Breakdown"
type: piechart
metric: clay_enrichments_total by (tier)
- name: "Cost per Enriched Lead"
type: stat
metric: clay_credits_used_total / clay_enrichments_total{status="enriched"}
```
### Step 5: Daily Summary Report
```typescript
// src/clay/daily-report.ts — generate daily enrichment summary
function generateDailyReport(collector: ClayMetricsCollector): void {
console.log(collector.getReport());
// Post to Slack
if (process.env.SLACK_WEBHOOK_URL) {
fetch(process.env.SLACK_WEBHOOK_URL, {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({
text: `*Daily Clay Enrichment Report*\n\`\`\`\n${collector.getReport()}\n\`\`\``,
}),
}).catch(console.error);
}
}
```
## Error Handling
| Issue | Cause | Solution |
|-------|-------|----------|
| Credits depleting fast | High waterfall depth or uncapped tables | Add credit burn alert, reduce waterfall |
| Hit rate near 0% | Invalid input data (personal domains, typos) | Add data quality monitoring, pre-filter |
| Missing metrics | Webhook handler not instrumented | Add metrics collection to callback handler |
| Dashboard shows stale data | Metrics not being pushed | Verify Prometheus scrape config |
## Resources
- [Prometheus Client Libraries](https://prometheus.io/docs/instrumenting/clientlibs/)
- [Grafana Dashboard Examples](https://grafana.com/grafana/dashboards/)
- [Clay University -- Actions & Data Credits](https://university.clay.com/docs/actions-data-credits)
## Next Steps
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