From clay-pack
Set up comprehensive observability for Clay integrations with metrics, traces, and alerts. Use when implementing monitoring for Clay operations, setting up dashboards, or configuring alerting for Clay integration health. Trigger with phrases like "clay monitoring", "clay metrics", "clay observability", "monitor clay", "clay alerts", "clay tracing".
How this skill is triggered — by the user, by Claude, or both
Slash command
/clay-pack:clay-observabilityThis skill is limited to the following tools:
The summary Claude sees in its skill listing — used to decide when to auto-load this skill
Monitor Clay data enrichment pipeline health, credit consumption velocity, and enrichment success rates. Clay's credit-based pricing model means observability must track per-enrichment costs (email lookup: ~1 credit, company enrichment: ~5 credits, waterfall enrichment: variable).
Monitor Clay data enrichment pipeline health, credit consumption velocity, and enrichment success rates. Clay's credit-based pricing model means observability must track per-enrichment costs (email lookup: ~1 credit, company enrichment: ~5 credits, waterfall enrichment: variable).
set -euo pipefail
# Query current credit usage by table
curl "https://api.clay.com/v1/workspace/usage?group_by=table&period=today" \
-H "Authorization: Bearer $CLAY_API_KEY" | \
jq '.usage[] | {table_name, credits_used, rows_enriched, avg_credits_per_row: (.credits_used / (.rows_enriched + 0.01))}'
// clay-enrichment-monitor.ts
async function monitorEnrichments() {
const tables = await clayApi.listTables();
for (const table of tables) {
const stats = await clayApi.getTableStats(table.id);
const hitRate = stats.rows_with_data / Math.max(stats.total_rows, 1) * 100;
emitGauge('clay_enrichment_hit_rate_pct', hitRate, { table: table.name, enrichment: stats.enrichment_type });
emitCounter('clay_credits_consumed', stats.credits_used, { table: table.name });
if (hitRate < 30) {
console.warn(`Low hit rate on ${table.name}: ${hitRate.toFixed(1)}% (check enrichment config)`);
}
}
}
groups:
- name: clay
rules:
- alert: ClayCreditBurnHigh
expr: rate(clay_credits_consumed[1h]) > 500 # HTTP 500 Internal Server Error
annotations: { summary: "Clay burning >500 credits/hour (projected monthly: {{ $value * 720 }})" } # 720: HTTP 500 Internal Server Error
- alert: ClayLowHitRate
expr: clay_enrichment_hit_rate_pct < 20
for: 30m
annotations: { summary: "Clay enrichment hit rate below 20% on {{ $labels.table }}" }
- alert: ClayCreditBalance
expr: clay_credits_remaining < 1000 # 1000: 1 second in ms
annotations: { summary: "Clay credit balance below 1,000 -- refill needed" }
{"ts":"2026-03-10T14:30:00Z","table":"outbound-leads","enrichment":"email_finder","rows_attempted":100,"rows_enriched":72,"credits_used":100,"hit_rate":72.0,"duration_ms":4500} # 2026: 4500 = configured value
Key panels: credit consumption by table (bar chart), enrichment hit rate by provider, daily/weekly credit burn trend, credits remaining gauge, and cost-per-enriched-row (credits used / rows with actual data returned). Tables with low hit rates and high credit burn are optimization targets.
| Issue | Cause | Solution |
|---|---|---|
| Credits depleting fast | Waterfall enrichment trying all providers | Limit waterfall steps or set credit cap per row |
| Hit rate near 0% | Bad input data (invalid emails/domains) | Clean input data before enrichment |
| API timeout on enrichment | Provider rate limit | Reduce table auto-enrich concurrency |
| Usage API returning stale data | Caching lag | Wait 5 minutes for usage data to update |
Basic usage: Apply clay observability to a standard project setup with default configuration options.
Advanced scenario: Customize clay observability for production environments with multiple constraints and team-specific requirements.
npx claudepluginhub terrylica/claude-code-plugins-plus --plugin clay-packGuides collaborative design exploration before implementation: explores context, asks clarifying questions, proposes approaches, and writes a design doc for user approval.
Creates structured, bite-sized implementation plans from specs or requirements before writing code. Useful for breaking down multi-step tasks into testable steps with file structure and task boundaries.
Synthesizes the current conversation into a structured spec (PRD) and publishes it to the project issue tracker with a ready-for-agent label, without interviewing the user.
4plugins reuse this skill
First indexed Jul 11, 2026