Automated summary
Sets up a monitoring stack for Windsurf API integrations covering Prometheus metrics, OpenTelemetry traces, structured logs, and AlertManager rules.
Strengths
- Ships ready-to-use prom-client counters, histograms, and gauges for requests, latency, errors, and rate-limit headroom
- Provides an instrumented wrapper that automatically records status, error type, and duration for each call
- Includes an OpenTelemetry span pattern with exception recording plus pino structured logging
- Offers concrete AlertManager rules for error rate and p95 latency thresholds
Limitations
- TypeScript/Node.js only — no examples for other languages or runtimes
- Assumes Prometheus, Grafana, AlertManager, and the OTel SDK are already deployed; no install steps or dashboard JSON included
- Snippets are illustrative (the alert file is truncated) and must be adapted to the real Windsurf API surface
Use it when you need to add metrics, traces, logs, or alerts around an existing Windsurf API integration.
Avoid it if you need a full observability platform rollout or instrumentation guidance for non-Node.js services.
Security analysis
SafeThe skill only provides observability setup guidance and code examples using Read/Write/Edit. It does not instruct destructive commands, secret exfiltration, obfuscated payloads, or safety bypasses.
No concerns found
How this analysis is madeExamples
Instrument my Windsurf API client with prom-client: a request counter labelled by method and status, a latency histogram, and an error counter by error type, exposed on a /metrics endpoint.Wrap every Windsurf API call in an OpenTelemetry span named windsurf.<operation>, record exceptions and set the span status on failure, following the windsurf-observability patterns.Write AlertManager rules that fire when the Windsurf error rate exceeds 5% over 5 minutes, or when p95 request latency goes above 2 seconds.name: windsurf-observability description: | Set up comprehensive observability for Windsurf integrations with metrics, traces, and alerts. Use when implementing monitoring for Windsurf operations, setting up dashboards, or configuring alerting for Windsurf integration health. Trigger with phrases like "windsurf monitoring", "windsurf metrics", "windsurf observability", "monitor windsurf", "windsurf alerts", "windsurf tracing". allowed-tools: Read, Write, Edit version: 1.0.0 license: MIT author: Jeremy Longshore jeremy@intentsolutions.io
Windsurf Observability
Overview
Set up comprehensive observability for Windsurf integrations.
Prerequisites
- Prometheus or compatible metrics backend
- OpenTelemetry SDK installed
- Grafana or similar dashboarding tool
- AlertManager configured
Metrics Collection
Key Metrics
| Metric | Type | Description |
|--------|------|-------------|
| windsurf_requests_total | Counter | Total API requests |
| windsurf_request_duration_seconds | Histogram | Request latency |
| windsurf_errors_total | Counter | Error count by type |
| windsurf_rate_limit_remaining | Gauge | Rate limit headroom |
Prometheus Metrics
import { Registry, Counter, Histogram, Gauge } from 'prom-client';
const registry = new Registry();
const requestCounter = new Counter({
name: 'windsurf_requests_total',
help: 'Total Windsurf API requests',
labelNames: ['method', 'status'],
registers: [registry],
});
const requestDuration = new Histogram({
name: 'windsurf_request_duration_seconds',
help: 'Windsurf request duration',
labelNames: ['method'],
buckets: [0.05, 0.1, 0.25, 0.5, 1, 2.5, 5],
registers: [registry],
});
const errorCounter = new Counter({
name: 'windsurf_errors_total',
help: 'Windsurf errors by type',
labelNames: ['error_type'],
registers: [registry],
});
Instrumented Client
async function instrumentedRequest<T>(
method: string,
operation: () => Promise<T>
): Promise<T> {
const timer = requestDuration.startTimer({ method });
try {
const result = await operation();
requestCounter.inc({ method, status: 'success' });
return result;
} catch (error: any) {
requestCounter.inc({ method, status: 'error' });
errorCounter.inc({ error_type: error.code || 'unknown' });
throw error;
} finally {
timer();
}
}
Distributed Tracing
OpenTelemetry Setup
import { trace, SpanStatusCode } from '@opentelemetry/api';
const tracer = trace.getTracer('windsurf-client');
async function tracedWindsurfCall<T>(
operationName: string,
operation: () => Promise<T>
): Promise<T> {
return tracer.startActiveSpan(`windsurf.${operationName}`, async (span) => {
try {
const result = await operation();
span.setStatus({ code: SpanStatusCode.OK });
return result;
} catch (error: any) {
span.setStatus({ code: SpanStatusCode.ERROR, message: error.message });
span.recordException(error);
throw error;
} finally {
span.end();
}
});
}
Logging Strategy
Structured Logging
import pino from 'pino';
const logger = pino({
name: 'windsurf',
level: process.env.LOG_LEVEL || 'info',
});
function logWindsurfOperation(
operation: string,
data: Record<string, any>,
duration: number
) {
logger.info({
service: 'windsurf',
operation,
duration_ms: duration,
...data,
});
}
Alert Configuration
Prometheus AlertManager Rules
# windsurf_alerts.yaml
groups:
- name: windsurf_alerts
rules:
- alert: WindsurfHighErrorRate
expr: |
rate(windsurf_errors_total[5m]) /
rate(windsurf_requests_total[5m]) > 0.05
for: 5m
labels:
severity: warning
annotations:
summary: "Windsurf error rate > 5%"
- alert: WindsurfHighLatency
expr: |
histogram_quantile(0.95,
rate(windsurf_request_duration_seconds_bucket[5m])
) > 2
for: 5m
labels:
severity: warning
annotations:
summary: "Windsurf P95 latency > 2s"
- alert: WindsurfDown
expr: up{job="windsurf"} == 0
for: 1m
labels:
severity: critical
annotations:
summary: "Windsurf integration is down"
Dashboard
Grafana Panel Queries
{
"panels": [
{
"title": "Windsurf Request Rate",
"targets": [{
"expr": "rate(windsurf_requests_total[5m])"
}]
},
{
"title": "Windsurf Latency P50/P95/P99",
"targets": [{
"expr": "histogram_quantile(0.5, rate(windsurf_request_duration_seconds_bucket[5m]))"
}]
}
]
}
Instructions
Step 1: Set Up Metrics Collection
Implement Prometheus counters, histograms, and gauges for key operations.
Step 2: Add Distributed Tracing
Integrate OpenTelemetry for end-to-end request tracing.
Step 3: Configure Structured Logging
Set up JSON logging with consistent field names.
Step 4: Create Alert Rules
Define Prometheus alerting rules for error rates and latency.
Output
- Metrics collection enabled
- Distributed tracing configured
- Structured logging implemented
- Alert rules deployed
Error Handling
| Issue | Cause | Solution | |-------|-------|----------| | Missing metrics | No instrumentation | Wrap client calls | | Trace gaps | Missing propagation | Check context headers | | Alert storms | Wrong thresholds | Tune alert rules | | High cardinality | Too many labels | Reduce label values |
Examples
Quick Metrics Endpoint
app.get('/metrics', async (req, res) => {
res.set('Content-Type', registry.contentType);
res.send(await registry.metrics());
});
Resources
Next Steps
For incident response, see windsurf-incident-runbook.
From the file to a first result
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View the source and supporting filesThis download contains SKILL.md only. Any scripts, references, templates and dependencies are not included. Get the required files from the source, preserving their directory structure, before continuing.
1. Download the file
Download SKILL.mdFrom the root of a test project, save the file as .skill-downloads/windsurf-observability-mm5t8cc4/SKILL.md, or use the command below. This folder is for inspecting the skill before installation.
Command for macOS/Linux or WSL: requires a POSIX shell and curl. On Windows without WSL, use the download button and create the folder manually.
mkdir -p '.skill-downloads/windsurf-observability-mm5t8cc4' && curl --fail --show-error --location 'https://skills-guides.com/api/skills/windsurf-observability-mm5t8cc4/download' --output '.skill-downloads/windsurf-observability-mm5t8cc4/SKILL.md.part' && mv '.skill-downloads/windsurf-observability-mm5t8cc4/SKILL.md.part' '.skill-downloads/windsurf-observability-mm5t8cc4/SKILL.md'2. Check prerequisites
Read SKILL.md before using it. If it references scripts or external services, inspect them and prepare the required access in your test environment.
Tools declared by the author (check availability in your agent): Read, Write, Edit
Original excerpt: Prerequisites
- Prometheus or compatible metrics backend
- OpenTelemetry SDK installed
- Grafana or similar dashboarding tool
- AlertManager configured
The platforms on this page are catalog indications. The paths below follow tool documentation; they do not prove this skill has been run in those tools. No minimum tool version is confirmed for this listing.
3. Load the skill
After inspection, copy the complete folder into your project using one of the commands below, then open a new tool session. The command stops if a folder with the same name already exists: compare the files before replacing it.
Claude Code
test -f '.skill-downloads/windsurf-observability-mm5t8cc4/SKILL.md' && test -s '.skill-downloads/windsurf-observability-mm5t8cc4/SKILL.md' && mkdir -p '.claude/skills' && test ! -e '.claude/skills/windsurf-observability' && cp -R '.skill-downloads/windsurf-observability-mm5t8cc4' '.claude/skills/windsurf-observability'OpenSkills
OpenSkills must already be installed. The local install/read procedure is checked with OpenSkills 1.5.0, which requires Node.js ≥ 20.6.0. Catalog slugs are not resolved automatically.
Official OpenSkills installationopenskills install './.skill-downloads/windsurf-observability-mm5t8cc4'openskills read 'windsurf-observability-mm5t8cc4'Reading should display the installed file content and its base directory. It does not run the skill or install its dependencies.
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4. Try a first task
Use a short, synthetic input: an API endpoint, a small document or an interface brief. In a new conversation, attach the file or give the agent its path, then adapt this request:
Read .skill-downloads/windsurf-observability-mm5t8cc4/SKILL.md and apply its instructions to this example: [describe a test input]. Identify any missing files, dependencies or access. Produce the result requested by the skill without inventing data or running unreviewed scripts.Expected result: output matching the skill instructions, or a precise list of missing prerequisites. A read confirmation alone does not validate a first use. If an external resource is unavailable, that path remains untested.
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