A set of rules for monitoring software in production. Monitoring means collecting logs, measurements, and request traces so developers can see how services behave.

It helps define structured logs, performance measurements, distributed request tracing, and alert severity levels.

It reduces the difficulty of finding slow requests, failures, and overloaded services. It also gives teams consistent rules for safe logs and alerts.

monitoring — Cursor rule for Cursor by girijashankarj/cursor-handbook

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Clone the repo

git clone --depth 1 https://github.com/girijashankarj/cursor-handbook

Made for: Cursor.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/rules/girijashankarj/cursor-handbook/monitoring/github.svg)](https://agentmods.dev/rules/girijashankarj/cursor-handbook/monitoring)

Your own site

<a href="https://agentmods.dev/rules/girijashankarj/cursor-handbook/monitoring"><img src="https://agentmods.dev/badge/rules/girijashankarj/cursor-handbook/monitoring/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/rules/girijashankarj/cursor-handbook/monitoring"><img src="https://agentmods.dev/badge/rules/girijashankarj/cursor-handbook/monitoring.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 565 This file is loaded in full into every session.

When invoked 565 The same file — it is already loaded in full.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00565	$0.00565
Opus 5.5	$0.00226	$0.00226
Sonnet 5.5	$0.00113	$0.00113
Haiku 4.5	$0.00056	$0.00056

Measured 1mo ago against content hash bc268713c20a, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

monitoring scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.cursor/rules/devops/monitoring.mdc · 68 lines

What it actually says

Monitoring & Observability Rules

Three Pillars of Observability

1. Logging

Structured JSON format for all logs
Every log entry MUST include: timestamp, level, correlationId, service
Log levels: ERROR → WARN → INFO → DEBUG
NEVER log PII, secrets, or full request/response bodies
Use sampling for high-volume debug logs in production

{
  "timestamp": "2026-01-15T10:30:00Z",
  "level": "info",
  "correlationId": "abc-123-def",
  "service": "{{CONFIG.project.name}}",
  "operation": "createOrder",
  "duration_ms": 245,
  "status": "success"
}

2. Metrics

Key metrics to track:

Request rate (requests/second)
Error rate (errors/total requests)
Latency (p50, p95, p99)
Saturation (CPU, memory, disk, connections)
Business metrics (orders/minute, signups/day)

3. Tracing

Implement distributed tracing across all services
Propagate trace context via headers (traceparent, tracestate)
Record spans for: HTTP calls, DB queries, cache operations, queue operations
Sample traces at 10% in production, 100% in staging

Alerting Rules

Severity Levels

Severity	Response Time	Example
P1 - Critical	15 min	Service down, data loss
P2 - High	1 hour	Degraded performance, partial outage
P3 - Medium	4 hours	Elevated error rate, slow queries
P4 - Low	Next business day	Warning thresholds, capacity planning

Alert Thresholds

Error rate > 1% for 5 minutes → P2
Error rate > 5% for 2 minutes → P1
p99 latency > 2s for 10 minutes → P3
CPU > 80% for 15 minutes → P3
Disk > 90% → P2
Service health check failure → P1

Dashboard Requirements

Every service MUST have a dashboard with:

Request rate and error rate over time
Latency percentiles (p50, p95, p99)
Resource utilization (CPU, memory)
Active connections / concurrent requests
Business-specific metrics

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

1mo ago First seen · 68 lines · 565 tokens per session scan A bc268713c20a

Subscribe to this mod's changes

monitoring is a cursor rule published in the GitHub repository girijashankarj/cursor-handbook (33 stars, last pushed 1mo ago), licensed MIT. It adds 565 tokens to every session, about $0.0023 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

Analytics and metrics Claude Code DevOps and cloud claude claude-ai cursor cursor-agents cursor-ai

monitoring