documenso-observability
Implements structured logging, latency tracking, and request monitoring for Documenso API integrations.
Install
mkdir -p .claude/skills/documenso-observability && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/8428" && unzip -o skill.zip -d .claude/skills/documenso-observability && rm skill.zipInstalls to .claude/skills/documenso-observability
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Implement monitoring, logging, and tracing for Documenso integrations.Key capabilities
- →Instrument Documenso API clients to track request counts and latency
- →Calculate error rates and status code distributions
- →Expose health check endpoints for monitoring systems
- →Provide Prometheus-compatible metrics for scraping
- →Log operations and errors with structured context
How it works
It uses a Proxy object to wrap the Documenso client, intercepting method calls to measure latency and track success or failure rates. Metrics are exposed via an endpoint for external monitoring tools to scrape.
Inputs & outputs
When to use documenso-observability
- →Implementing API request tracing
- →Monitoring error rates
- →Tracking integration latency
- →Debugging production issues
About this skill
Documenso Observability
Overview
Implement monitoring, structured logging, and health checks for Documenso integrations. Since Documenso does not expose rate limit headers or usage metrics via API, observability is built around your API call patterns, latency, error rates, and webhook delivery.
Prerequisites
- Working Documenso integration
- Monitoring stack (Prometheus/Grafana, Datadog, or CloudWatch)
- Logging infrastructure
Instructions
Step 1: Instrumented Client Wrapper
// src/observability/documenso-metrics.ts
import { Documenso } from "@documenso/sdk-typescript";
interface Metrics {
requestCount: number;
errorCount: number;
totalLatencyMs: number;
errorsByStatus: Record<number, number>;
}
const metrics: Metrics = {
requestCount: 0,
errorCount: 0,
totalLatencyMs: 0,
errorsByStatus: {},
};
export function createInstrumentedClient(): Documenso {
const client = new Documenso({ apiKey: process.env.DOCUMENSO_API_KEY! });
return new Proxy(client, {
get(target, prop) {
const value = (target as any)[prop];
if (typeof value === "object" && value !== null) {
return new Proxy(value, {
get(innerTarget, method) {
const fn = (innerTarget as any)[method];
if (typeof fn !== "function") return fn;
return async (...args: any[]) => {
const start = Date.now();
metrics.requestCount++;
try {
const result = await fn.apply(innerTarget, args);
metrics.totalLatencyMs += Date.now() - start;
return result;
} catch (err: any) {
metrics.errorCount++;
const status = err.statusCode ?? 0;
metrics.errorsByStatus[status] = (metrics.errorsByStatus[status] || 0) + 1;
metrics.totalLatencyMs += Date.now() - start;
throw err;
}
};
},
});
}
return value;
},
});
}
// Expose metrics for Prometheus scraping
export function getMetrics() {
return {
...metrics,
avgLatencyMs: metrics.requestCount > 0
? Math.round(metrics.totalLatencyMs / metrics.requestCount)
: 0,
errorRate: metrics.requestCount > 0
? (metrics.errorCount / metrics.requestCount * 100).toFixed(2) + "%"
: "0%",
};
}
Step 2: Structured Logging
// src/observability/logger.ts
import { createLogger, format, transports } from "winston";
const logger = createLogger({
level: process.env.LOG_LEVEL ?? "info",
format: format.combine(
format.timestamp(),
format.json()
),
defaultMeta: { service: "documenso-integration" },
transports: [
new transports.Console(),
// Add file or cloud transport for production
],
});
// Log Documenso operations with structured context
export function logDocumensoOperation(
operation: string,
documentId?: number,
extra?: Record<string, any>
) {
logger.info("documenso_operation", {
operation,
documentId,
...extra,
});
}
// Log errors with full context
export function logDocumensoError(
operation: string,
error: any,
documentId?: number
) {
logger.error("documenso_error", {
operation,
documentId,
statusCode: error.statusCode,
message: error.message,
// Never log API keys
});
}
Step 3: Health Check Endpoint
// src/api/health.ts
import { Documenso } from "@documenso/sdk-typescript";
interface HealthStatus {
status: "healthy" | "degraded" | "unhealthy";
latencyMs: number;
message: string;
}
async function checkDocumensoHealth(): Promise<HealthStatus> {
const client = new Documenso({ apiKey: process.env.DOCUMENSO_API_KEY! });
const start = Date.now();
try {
await client.documents.findV0({ page: 1, perPage: 1 });
const latencyMs = Date.now() - start;
if (latencyMs > 5000) {
return { status: "degraded", latencyMs, message: "High latency" };
}
return { status: "healthy", latencyMs, message: "OK" };
} catch (err: any) {
return {
status: "unhealthy",
latencyMs: Date.now() - start,
message: `${err.statusCode ?? "unknown"}: ${err.message}`,
};
}
}
// Express endpoint
app.get("/health/documenso", async (req, res) => {
const health = await checkDocumensoHealth();
const httpStatus = health.status === "healthy" ? 200 : health.status === "degraded" ? 200 : 503;
res.status(httpStatus).json(health);
});
Step 4: Prometheus Metrics Endpoint
// src/api/metrics.ts
import { getMetrics } from "../observability/documenso-metrics";
app.get("/metrics/documenso", (req, res) => {
const m = getMetrics();
res.type("text/plain").send(`
# HELP documenso_requests_total Total API requests
# TYPE documenso_requests_total counter
documenso_requests_total ${m.requestCount}
# HELP documenso_errors_total Total API errors
# TYPE documenso_errors_total counter
documenso_errors_total ${m.errorCount}
# HELP documenso_avg_latency_ms Average request latency
# TYPE documenso_avg_latency_ms gauge
documenso_avg_latency_ms ${m.avgLatencyMs}
`.trim());
});
Step 5: Webhook Delivery Monitoring
// Track webhook delivery success/failure
const webhookMetrics = {
received: 0,
processed: 0,
failed: 0,
byEvent: {} as Record<string, number>,
};
app.post("/webhooks/documenso", async (req, res) => {
webhookMetrics.received++;
const { event } = req.body;
webhookMetrics.byEvent[event] = (webhookMetrics.byEvent[event] || 0) + 1;
res.status(200).json({ received: true });
try {
await processWebhookEvent(req.body);
webhookMetrics.processed++;
} catch (err) {
webhookMetrics.failed++;
logDocumensoError("webhook_processing", err);
}
});
// Expose webhook metrics
app.get("/metrics/webhooks", (req, res) => {
res.json(webhookMetrics);
});
Step 6: Alerting Rules
# alerting-rules.yml (Prometheus)
groups:
- name: documenso
rules:
- alert: DocumensoHighErrorRate
expr: rate(documenso_errors_total[5m]) / rate(documenso_requests_total[5m]) > 0.05
for: 5m
labels:
severity: warning
annotations:
summary: "Documenso error rate above 5%"
- alert: DocumensoUnhealthy
expr: up{job="documenso-health"} == 0
for: 2m
labels:
severity: critical
annotations:
summary: "Documenso health check failing"
- alert: DocumensoHighLatency
expr: documenso_avg_latency_ms > 5000
for: 5m
labels:
severity: warning
annotations:
summary: "Documenso average latency above 5s"
Key Metrics to Monitor
| Metric | Healthy | Warning | Critical |
|---|---|---|---|
| API error rate | < 1% | 1-5% | > 5% |
| Average latency | < 1s | 1-5s | > 5s |
| Health check | Passing | Degraded | Failing |
| Webhook delivery | > 99% | 95-99% | < 95% |
Error Handling
| Observability Issue | Cause | Solution |
|---|---|---|
| Metrics not appearing | Scrape config wrong | Verify Prometheus targets |
| Logs missing | Log level too high | Set LOG_LEVEL=debug temporarily |
| False alerts | Thresholds too sensitive | Adjust to match your traffic patterns |
| Health check flapping | Transient network issues | Add for: 2m to alert rules |
Resources
Next Steps
For incident response, see documenso-incident-runbook.
When not to use it
- →When logging sensitive information like API keys
- →When the integration lacks a monitoring stack for scraping
Prerequisites
Limitations
- →Documenso does not expose rate limit headers via API
- →Health check latency threshold is fixed at 5000ms
How it compares
Unlike manual logging, this approach uses a Proxy wrapper to automatically instrument all API methods without modifying individual service calls.
Compared to similar skills
documenso-observability side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| documenso-observability (this skill) | 0 | 25d | Review | Intermediate |
| perplexity-observability | 1 | 25d | No flags | Intermediate |
| setup-sap-btp-logging | 0 | 6mo | Review | Beginner |
| mcp-builder | 136 | 3mo | Review | Advanced |
Try saying
Example prompts that trigger this skill in your AI assistant.
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