Distributed Trace Analysis

by naodeng

Distributed Trace Analysis is a Quality skill for Claude Code, published by naodeng in awesome-qa-skills.

193 stars27 forkson naodeng/awesome-qa-skillsAdded 2026/09/05+1% in starsRepository updated 2026/09/03

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Install in seconds

Install Distributed Trace Analysis

Copy Distributed Trace Analysis into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.

terminal

npx degit https://github.com/naodeng/awesome-qa-skills/tree/main/skills/en/testing-types/distributed-trace-analysis ~/.claude/skills/distributed-trace-analysis

Requires Node.js. Downloads this skill only — not the rest of the repository — into your Claude Code skills folder.

Without Node.js

git clone https://github.com/naodeng/awesome-qa-skills.git

Clones the whole repository, then copy the skill’s own directory into your skills folder yourself.

In this catalog

Source file: skills/en/testing-types/distributed-trace-analysis/SKILL.md in naodeng/awesome-qa-skills
Installs to: ~/.claude/skills/distributed-trace-analysis
Collection: One of 25 skills cataloged from this repository
Category: Quality — 1662 skills

What Distributed Trace Analysis does

Distributed Trace Analysis reviews traces, spans, and topology to find cross-service latency, error propagation, retries, and dependency failures. Use it when evidence is incomplete but a bounded first pass or review artifact is still needed.

Distributed Trace Analysis is cataloged under Quality on DirSkills. Distributed Trace Analysis comes from a repository tagged agent-skills, ai-qa, ai-skills, ai-testing and ai-tools.

Documentation

README

Excerpt

Distributed Trace Analysis

When to Use

Use this skill when you need to use traces, spans, and topology to locate cross-service latency, error propagation, and dependency failures.
Use it to review an existing plan, result, or evidence set and produce actionable improvements.
Use it when context is incomplete but a bounded first pass is still valuable.

Output Format Options

Default to Markdown for review, execution, and incremental refinement.
When the user requests tables, CSV, JSON, or ticket fields, preserve risk, evidence, priority, and boundary information.
For machine-consumed output, confirm the schema, enums, and required fields first.

How to Use

This is the opening of the README. Read the full README on GitHub.

Frequently asked about Distributed Trace Analysis

What else does naodeng publish alongside Distributed Trace Analysis?
Distributed Trace Analysis is one of 25 skills that DirSkills catalogs from naodeng/awesome-qa-skills, the repository it ships in. Its siblings there include AI Agent Testing, AI Feature Testing and AI-Assisted Testing. Each one is a separate skill with its own page in this directory, installs the same way Distributed Trace Analysis does, and is maintained by naodeng in that same repository. The rest of the collection is listed on the naodeng/awesome-qa-skills page.
How does Distributed Trace Analysis compare to other Quality skills?
Distributed Trace Analysis ranks #1567 by stars among the 1662 Quality skills in this catalog. The most-starred ones next to it are Benchmark, Benchmark Optimization Loop and API Design Patterns. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of Distributed Trace Analysis against them. Open each page to compare what they document and how they install.