Skills distributed-tracing

📦

distributed-tracing

Name: distributed-tracing
Author: sickn33

Content revision r1 Low Risk ⚡ Contains scripts⚙️ External commands🌐 Network access

Implement Distributed Tracing

Microservice teams need clear request paths across services. This skill guides Jaeger, Tempo, OpenTelemetry instrumentation, sampling, and troubleshooting.

Supports: Claude Codex Code(CC)

📊 74 Adequate

Install with my Agent

Copy this request to your Agent. It includes the canonical Skill page and manifest.

Agent request

Review the Skillstore skill "distributed-tracing" from https://skillstore.io/skills/sickn33-distributed-tracing.md and its manifest at https://skillstore.io/api/skills/sickn33-distributed-tracing/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.

Your Agent should still show its plan and request any confirmation required by the security policy.

Agent-readable resources

Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.

Markdown detail GET /skills/sickn33-distributed-tracing.md Signed manifest GET /api/skills/sickn33-distributed-tracing/manifest Signed lockfile GET /api/skills/sickn33-distributed-tracing/lockfile

Test it

Using "distributed-tracing". Trace a slow checkout request across five services.

Expected outcome:

A step-by-step tracing plan with service spans, latency attributes, sampling guidance, and Jaeger queries for slow operations.

Using "distributed-tracing". Prepare tracing for a new payments service.

Expected outcome:

An instrumentation checklist covering service names, span boundaries, error recording, context propagation, and production validation.

Using "distributed-tracing". No traces appear after deployment.

Expected outcome:

A troubleshooting path that checks collector endpoints, exporter configuration, sampling settings, network reachability, and application logs.

Security Audit

Low Risk

v6 • 7/9/2026 Open versioned report

Most static findings are false positives from Markdown code fences, inline file references, and language examples rather than executable skill code. The Kubernetes setup example does include a remote manifest application flow, which should require review and explicit approval before use. I also found a low-severity privacy concern around recommending user_id trace tags without minimization guidance.

Files scanned

459

Lines analyzed

Review items

False positives ignored

Confirmed security concerns (1)

Low

SKILL.md:401

Potential PII in Trace Attributes

The best practices recommend adding user_id as a trace tag. User identifiers in traces can expose personal data unless they are minimized, pseudonymized, and protected by retention and access controls.

The recommendation explicitly names user_id as trace metadata. This can be legitimate observability practice, but it creates a privacy risk without safeguards.

Capability review items (2)

These are real local capabilities that may be expected for this skill, so they require review but are not counted as confirmed malicious behavior.

Medium

SKILL.md:62-84

Ruby/shell backtick execution

```bash

The fenced bash setup includes kubectl commands that create Kubernetes resources and apply a remote Jaeger manifest. This is legitimate documentation, but it is operationally sensitive if executed without user approval.

Low

SKILL.md:65

Hardcoded URL

kubectl create -f https://github.com/jaegertracing/jaeger-operator/releases/download/v1.51.0/jaeger-

The setup command references a remote GitHub release manifest that would be fetched and applied to a Kubernetes cluster. The source appears legitimate, but remote deployment manifests require review and integrity controls.

Risk Factors

⚡ Contains scripts (1)

SKILL.md:206-213

⚙️ External commands (41)

🌐 Network access (9)

SKILL.md:282 SKILL.md:420 SKILL.md:272 SKILL.md:65 SKILL.md:80 SKILL.md:171 SKILL.md:217 SKILL.md:272 SKILL.md:282

Audited by: codex View Audit History →

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Open versioned report

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https://skillstore.io/skills/sickn33-distributed-tracing/audits/6?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_report

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Academic citations (APA · BibTeX · CFF)

APA citation

sickn33. (2026). distributed-tracing security audit report (audit version 6) [Author version unspecified]. Skillstore. https://skillstore.io/skills/sickn33-distributed-tracing/audits/6

BibTeX citation

@techreport{sickn33-sickn33-distributed-tracing-2026,
  author = {sickn33},
  title = {distributed-tracing security audit report (audit version 6)},
  institution = {Skillstore},
  year = {2026},
  number = {6},
  url = {https://skillstore.io/skills/sickn33-distributed-tracing/audits/6},
  note = {Author version unspecified}
}

CITATION.cff

cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "distributed-tracing security audit report (audit version 6)"
version: "unspecified"
type: report
authors:
  - name: "sickn33"
date-released: "2026-07-09"
url: "https://skillstore.io/skills/sickn33-distributed-tracing/audits/6"
identifiers:
  - type: other
    value: "skillstore:sickn33-distributed-tracing:audit:6"
    description: "Skillstore immutable audit report identifier"

Compare variants

2 installable variants

Each author remains a separate installable skill. The recommended variant is ranked by Skillstore evidence.

Why this variant is first

Highest Skillstore Score

Author / source Skillstore Score Evidence Confidence Skillstore usage Updated

sickn33 Recommended Current

sickn33-distributed-tracing

Skillstore Score 74

Evidence Confidence High

Skillstore usage 8

Updated

2026-08-21

wshobson

wshobson-distributed-tracing

Skillstore Score 69

Evidence Confidence High

Skillstore usage 11

Updated

2026-08-21

Skillstore Score

Why this score Evidence Confidence: High

Architecture

Maintainability

Content

Community

Spec Compliance

What You Can Build

Debug Slow Requests

Map a request across frontend, gateway, service, and database spans to find latency sources.

Plan Tracing Rollout

Choose Jaeger or Tempo setup patterns, sampling rates, and instrumentation points for a service platform.

Improve Incident Analysis

Correlate traces, errors, and logs so incident teams can follow failure propagation across services.

Try These Prompts

Explain Trace Basics

Explain how traces, spans, context propagation, tags, and logs work in a microservice request path.

Design A Tracing Plan

Create a distributed tracing plan for these services: [services]. Include span names, key attributes, and propagation boundaries.

Configure Jaeger Or Tempo

Recommend a Jaeger or Tempo setup for [environment]. Include storage, collectors, sampling, and validation checks.

Diagnose Trace Gaps

Analyze why traces are missing between [service A] and [service B]. Check propagation, exporters, sampling, network paths, and logs.

Best Practices

Start with critical request paths before instrumenting every operation.
Use consistent service names, span names, and approved attributes.
Validate sampling, exporter health, and trace visibility in each environment.

Avoid

Adding high-cardinality or personal data to spans without controls.
Copying example endpoints or storage settings directly into production.
Running cluster setup commands without reviewing manifests and permissions.

Frequently Asked Questions

What tracing tools does this skill cover?

It covers Jaeger, Grafana Tempo, and OpenTelemetry instrumentation patterns.

Can it help with Python, Node.js, and Go services?

Yes. It includes examples for Flask, Express, and Go OpenTelemetry tracing.

Does it deploy tracing infrastructure automatically?

No. It provides setup guidance that must be reviewed before commands are run.

Is it suitable for production systems?

Yes, after adapting storage, sampling, security, retention, and access controls to the environment.

Can it troubleshoot missing traces?

Yes. It suggests checks for collector endpoints, network connectivity, sampling, exporters, and application logs.

How should sensitive data be handled?

Avoid raw personal data in spans. Use approved attributes, pseudonymous identifiers, and restricted trace access.

Developer Details

Author

sickn33

License

MIT

Skillstore revision

Version notice

The author did not declare a version.

Repository

https://github.com/sickn33/antigravity-awesome-skills/tree/main/skills/distributed-tracing

Ref

3e4b6c31a74a3bd1a291c98cf585d720cb9fbc88

Maintenance freshness

7/18/2026

Usage

8 downloads · 92 views

File structure

📄 SKILL.md