managing-lightstep

name	managing-lightstep
description	Use when working with Lightstep — lightstep (now ServiceNow Cloud Observability) platform for distributed tracing, service health monitoring, change intelligence, and SLOs. Covers querying traces, analyzing service performance, reviewing deployments, managing alert conditions, and SLO tracking. Use when investigating latency regressions, analyzing service dependencies, or managing observability configurations.
connection_type	lightstep
preload	false

Lightstep Monitoring Skill

Query, analyze, and manage Lightstep observability data using the Lightstep API.

API Overview

Lightstep uses a REST API at https://api.lightstep.com.

Core Helper Function

#!/bin/bash

ls_api() {
    local method="$1"
    local endpoint="$2"
    local data="${3:-}"
    local org="$LIGHTSTEP_ORG"
    local project="$LIGHTSTEP_PROJECT"
    local url="https://api.lightstep.com/public/v0.2/${org}/projects/${project}/${endpoint}"
    if [ -n "$data" ]; then
        curl -s -X "$method" "$url" \
            -H "Authorization: Bearer $LIGHTSTEP_API_KEY" \
            -H "Content-Type: application/json" \
            -d "$data"
    else
        curl -s -X "$method" "$url" \
            -H "Authorization: Bearer $LIGHTSTEP_API_KEY"
    fi
}

MANDATORY: Discovery-First Pattern

Always discover services, streams, and conditions before querying.

Phase 1: Discovery

#!/bin/bash

echo "=== Services ==="
ls_api GET "services" | jq -r '.data[] | "\(.id)\t\(.attributes.name)"' | head -20

echo ""
echo "=== Streams (Saved Queries) ==="
ls_api GET "streams" | jq -r '.data[] | "\(.id)\t\(.attributes.name)\t\(.attributes.query)"' | head -20

echo ""
echo "=== Alert Conditions ==="
ls_api GET "conditions" | jq -r '.data[] | "\(.id)\t\(.attributes.name)\t\(.attributes.expression)"' | head -15

echo ""
echo "=== SLOs ==="
ls_api GET "slos" | jq -r '.data[] | "\(.id)\t\(.attributes.name)\t\(.attributes.objective_percentage)%"' | head -15

Phase 2: Analysis

#!/bin/bash
SERVICE="${1:?Service name required}"

echo "=== Service Health ==="
ls_api GET "services/${SERVICE}" | jq -r '.data.attributes | "Latency P50: \(.latency_p50 // "N/A")ms\nLatency P99: \(.latency_p99 // "N/A")ms\nError Rate: \(.error_rate // "N/A")%\nOps/sec: \(.ops_per_sec // "N/A")"'

echo ""
echo "=== Recent Exemplar Traces ==="
ls_api GET "stored-traces?filter=service%3D${SERVICE}&limit=10" \
    | jq -r '.data[] | "\(.attributes.start_time[0:19])\t\(.attributes.duration_micros/1000)ms\t\(.attributes.root_span_name)"' | head -10

echo ""
echo "=== Service Dependencies ==="
ls_api GET "services/${SERVICE}/dependencies" \
    | jq -r '.data[] | "\(.attributes.direction)\t\(.attributes.name)\t\(.attributes.ops_per_sec) ops/s"' | head -15

echo ""
echo "=== Firing Conditions ==="
ls_api GET "conditions" | jq -r '.data[] | select(.attributes.state == "firing") | "\(.id)\t\(.attributes.name)\t\(.attributes.expression)"' | head -10

Output Rules

• TOKEN EFFICIENCY: Target ≤50 lines — use limit query params and head in output
• Use service-level aggregations before drilling into traces
• Check service health before querying individual spans

Output Format

Present results as a structured report:

Managing Lightstep Report
═════════════════════════
Resources discovered: [count]

Resource       Status    Key Metric    Issues
──────────────────────────────────────────────
[name]         [ok/warn] [value]       [findings]

Summary: [total] resources | [ok] healthy | [warn] warnings | [crit] critical
Action Items: [list of prioritized findings]

Target ≤50 lines of output. Use tables for multi-resource comparisons.

Anti-Hallucination Rules

1. NEVER assume resource names — always discover via CLI/API in Phase 1 before referencing in Phase 2.
2. NEVER fabricate metric names or dimensions — verify against the service documentation or --help output.
3. NEVER mix CLI commands between service versions — confirm which version/API you are targeting.
4. ALWAYS use the discovery → verify → analyze chain — every resource referenced must have been discovered first.
5. ALWAYS handle empty results gracefully — an empty response is valid data, not an error to retry.

Counter-Rationalizations

Shortcut	Counter	Why
"I'll skip discovery and check known resources"	Always run Phase 1 discovery first	Resource names change, new resources appear — assumed names cause errors
"The user only asked for a quick check"	Follow the full discovery → analysis flow	Quick checks miss critical issues; structured analysis catches silent failures
"Default configuration is probably fine"	Audit configuration explicitly	Defaults often leave logging, security, and optimization features disabled
"Metrics aren't needed for this"	Always check relevant metrics when available	API/CLI responses show current state; metrics reveal trends and intermittent issues
"I don't have access to that"	Try the command and report the actual error	Assumed permission failures prevent useful investigation; actual errors are informative