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.
npx skills add LiHongwei-cn/lihongwei-cn --skill distributed-tracinggit clone --depth 1 https://github.com/LiHongwei-cn/lihongwei-cnWrote 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.
[](https://agentmods.dev/skills/lihongwei-cn/lihongwei-cn/distributed-tracing)<a href="https://agentmods.dev/skills/lihongwei-cn/lihongwei-cn/distributed-tracing"><img src="https://agentmods.dev/badge/skills/lihongwei-cn/lihongwei-cn/distributed-tracing/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.
<a href="https://agentmods.dev/skills/lihongwei-cn/lihongwei-cn/distributed-tracing"><img src="https://agentmods.dev/badge/skills/lihongwei-cn/lihongwei-cn/distributed-tracing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00020 | $0.02649 |
| Opus 5.5 | $0.00008 | $0.01060 |
| Sonnet 5.5 | $0.00004 | $0.00530 |
| Haiku 4.5 | $0.00002 | $0.00265 |
Grade A, and why
distributed-tracing scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
response = requests.get('http://downstream-service/api', headers=headers) How it starts
The opening of the file, as written. The whole thing — 459 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Distributed Tracing
Implement distributed tracing with Jaeger and Tempo for request flow visibility across microservices.
Do not use this skill when
- The task is unrelated to distributed tracing
- You need a different domain or tool outside this scope
Instructions
- Clarify goals, constraints, and required inputs.
- Apply relevant best practices and validate outcomes.
- Provide actionable steps and verification.
- If detailed examples are required, open
resources/implementation-playbook.md.
Purpose
Track requests across distributed systems to understand latency, dependencies, and failure points.
Use this skill when
- Debug latency issues
- Understand service dependencies
- Identify bottlenecks
- Trace error propagation
- Analyze request paths
Distributed Tracing Concepts
Trace Structure
Trace (Request ID: abc123)
↓
Span (frontend) [100ms]
↓
Span (api-gateway) [80ms]
├→ Span (auth-service) [10ms]
└→ Span (user-service) [60ms]
└→ Span (database) [40ms]
Key Components
- Trace - End-to-end request journey
- Span - Single operation within a trace
- Context - Metadata propagated between services
- Tags - Key-value pairs for filtering
- Logs - Timestamped events within a span
Jaeger Setup
Kubernetes Deployment
# Deploy Jaeger Operator
kubectl create namespace observability
kubectl create -f https://github.com/jaegertracing/jaeger-operator/releases/download/v1.51.0/jaeger-operator.yaml -n observability
# Deploy Jaeger instance
kubectl apply -f - <<EOF
apiVersion: jaegertracing.io/v1
kind: Jaeger
metadata:
name: jaeger
namespace: observability
spec:
strategy: production
storage:
type: elasticsearch
options:
es:
server-urls: http://elasticsearch:9200
ingress:
enabled: true
EOF
Docker Compose
version: '3.8'
services:
jaeger:
image: jaegertracing/all-in-one:latest
ports:
- "5775:5775/udp"
- "6831:6831/udp"
- "6832:6832/udp"
- "5778:5778"
- "16686:16686" # UI
- "14268:14268" # Collector
- "14250:14250" # gRPC
- "9411:9411" # Zipkin
environment:
- COLLECTOR_ZIPKIN_HOST_PORT=:9411
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 · 459 lines · 20 tokens per session scan A 51595c2d16e4
distributed-tracing is a skill published in the GitHub repository LiHongwei-cn/lihongwei-cn (5 stars, last pushed 20d ago), licensed MIT. It adds 20 tokens to every session and 2,649 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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