Install
$ agentstack add skill-majiayu000-spellbook-observability-sre ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ● Environment & secrets Used
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
Observability & Site Reliability Engineering
Core Principles
- Three Pillars — Metrics, Logs, and Traces provide holistic visibility
- Observability-First — Build systems that explain their own behavior
- SLO-Driven — Define reliability targets that matter to users
- Proactive Detection — Find issues before customers do
- Blameless Culture — Learn from failures without blame
- Automate Toil — Reduce repetitive operational work
- Continuous Improvement — Each incident makes systems more resilient
- Full-Stack Visibility — Monitor from infrastructure to business metrics
Hard Rules (Must Follow)
> These rules are mandatory. Violating them means the skill is not working correctly.
Symptom-Based Alerts Only
Alert on user-facing symptoms, not internal infrastructure metrics.
# ❌ FORBIDDEN: Alerting on internal metrics
- alert: CPUHigh
expr: cpu_usage > 70%
# Users don't care about CPU, they care about latency
- alert: MemoryHigh
expr: memory_usage > 80%
# Internal metric, may not affect users
# ✅ REQUIRED: Alert on user experience
- alert: APILatencyHigh
expr: slo:api_latency:p95 > 0.200
annotations:
summary: "Users experiencing slow response times"
- alert: ErrorRateHigh
expr: slo:api_errors:rate5m > 0.001
annotations:
summary: "Users encountering errors"
Low Cardinality Labels
**Loki/Prometheus labels must have low cardinality ( { try { // Add business context span.setAttributes({ 'order.id': orderId, 'payment.amount': amount, 'payment.currency': 'USD', });
// Child span for external API call const paymentResult = await tracer.startActiveSpan('stripe.charge', async (childSpan) => { const result = await stripe.charges.create({ amount, currency: 'usd' }); childSpan.setAttribute('stripe.charge_id', result.id); childSpan.setStatus({ code: SpanStatusCode.OK }); childSpan.end(); return result; });
span.setStatus({ code: SpanStatusCode.OK }); return paymentResult; } catch (error) { span.recordException(error); span.setStatus({ code: SpanStatusCode.ERROR, message: error.message }); throw error; } finally { span.end(); } }); }
### Sampling Strategies
```yaml
# OpenTelemetry Collector config
processors:
# Probabilistic sampling: Keep 10% of traces
probabilistic_sampler:
sampling_percentage: 10
# Tail sampling: Make decisions after seeing full trace
tail_sampling:
policies:
# Always sample errors
- name: error-traces
type: status_code
status_code: {status_codes: [ERROR]}
# Always sample slow requests
- name: slow-traces
type: latency
latency: {threshold_ms: 1000}
# Sample 5% of normal traffic
- name: normal-traces
type: probabilistic
probabilistic: {sampling_percentage: 5}
Context Propagation
// Ensure trace context flows across services
import { propagation, context } from '@opentelemetry/api';
// Outgoing HTTP request (automatic with auto-instrumentation)
fetch('https://api.example.com/data', {
headers: {
// W3C Trace Context headers injected automatically:
// traceparent: 00---01
// tracestate: vendor=value
},
});
// Manual propagation for non-HTTP (e.g., message queues)
const carrier = {};
propagation.inject(context.active(), carrier);
await publishMessage(queue, { data: payload, headers: carrier });
Structured Logging Best Practices
JSON Logging Format
// Use structured logging library
import pino from 'pino';
const logger = pino({
level: process.env.LOG_LEVEL || 'info',
formatters: {
level: (label) => ({ level: label }),
},
timestamp: pino.stdTimeFunctions.isoTime,
// Include trace context in logs
mixin() {
const span = trace.getActiveSpan();
if (!span) return {};
const { traceId, spanId } = span.spanContext();
return {
trace_id: traceId,
span_id: spanId,
};
},
});
// Structured logging with context
logger.info(
{
user_id: '123',
order_id: 'ord_456',
amount: 99.99,
payment_method: 'card',
},
'Payment processed successfully'
);
// Output:
// {"level":"info","time":"2025-01-15T10:30:00.000Z","trace_id":"abc123","span_id":"def456","user_id":"123","order_id":"ord_456","amount":99.99,"payment_method":"card","msg":"Payment processed successfully"}
Log Levels
// Follow standard severity levels
logger.trace({ details }, 'Low-level debugging'); // Very verbose
logger.debug({ state }, 'Debug information'); // Development
logger.info({ event }, 'Normal operation'); // Production default
logger.warn({ issue }, 'Warning condition'); // Potential issues
logger.error({ error, context }, 'Error occurred'); // Errors
logger.fatal({ critical }, 'Fatal error'); // Process crash
Grafana Loki Configuration
# Promtail config - ships logs to Loki
server:
http_listen_port: 9080
positions:
filename: /tmp/positions.yaml
clients:
- url: http://loki:3100/loki/api/v1/push
scrape_configs:
- job_name: kubernetes
kubernetes_sd_configs:
- role: pod
relabel_configs:
# Add pod labels as Loki labels (LOW cardinality only!)
- source_labels: [__meta_kubernetes_namespace]
target_label: namespace
- source_labels: [__meta_kubernetes_pod_name]
target_label: pod
- source_labels: [__meta_kubernetes_pod_label_app]
target_label: app
pipeline_stages:
# Parse JSON logs
- json:
expressions:
level: level
trace_id: trace_id
# Extract fields as labels
- labels:
level:
trace_id:
Loki Best Practices
- Low Cardinality Labels — Use only 5-10 labels (namespace, app, level)
- High Cardinality in Log Body — Put userid, orderid in JSON, not labels
- LogQL for Filtering — Use
{app="api"} | json | user_id="123" - Retention Policy — Keep recent logs longer, compress old logs
# LogQL query examples
{namespace="production", app="api"} |= "error" # Text search
{app="api"} | json | level="error" | line_format "{{.msg}}" # JSON parsing
rate({app="api"}[5m]) # Log rate per second
sum by (level) (count_over_time({namespace="production"}[1h])) # Count by level
Extended Reference
Detailed material starting at ## SLO/SLI/SLA Management has been moved to [reference/extended.md](reference/extended.md) to keep this skill concise. Load that reference when the task requires the moved examples, command catalogs, checklists, platform details, or implementation templates.
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: majiayu000
- Source: majiayu000/spellbook
- License: MIT
- Homepage: https://github.com/majiayu000/spellbook#quick-start
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.