Agent skill

Distributed Tracing

by wshobson in wshobson/agents

Implement distributed tracing with Jaeger and Tempo to track requests across microservices and identify performance bottlenecks.

MITAuto-check passedDevOps & Cloud

Install Distributed Tracing

skills CLI
$ npx skills add wshobson/agents --skill distributed-tracing -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install wshobson/agents distributed-tracing --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/wshobson/agents.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/observability-monitoring/skills/distributed-tracing .claude/skills/distributed-tracing && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
distributed-tracing
GitHub stars
40k
Used in
12 other repos
Token cost
~527 tokens
SKILL.md length
174 words
Files
2 (incl. references)
Skills in repo
142
Repo updated
First seen
Licence
MIT

At a glance

Implement distributed tracing with Jaeger and Tempo to track requests across microservices and identify performance bottlenecks.

  • Works in 10 steps: Sample appropriately (1-10% in production) → Add meaningful tags (user_id, request_id) → Propagate context across all service… → …
  • Debugging microservices
  • SKILL.md covers Purpose, When to Use, Detailed patterns and worked… and Best Practices, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Distributed Tracing is an agent skill from wshobson/agents. Implement distributed tracing with Jaeger and Tempo to track requests across microservices and identify performance bottlenecks. Use when debugging microservices, analyzing request flows, or implementing observability for distributed systems.

Its SKILL.md is about 530 tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/details.md`).

It sits in DevOps & Cloud, covering Observability and Microservices. The repository describes itself as: Multi-harness agentic plugin marketplace for Claude Code, Codex, Cursor, OpenCode, GitHub Copilot, Google Antigravity, and Pi. The licence is MIT.

When your agent uses it

  • Debugging microservices
  • Analyzing request flows
  • Implementing observability for distributed systems

Example prompts

  • “/distributed-tracing”

Requirements

  • Python 3

Workflow steps

10 steps, taken from the first numbered list in SKILL.md.

  1. Sample appropriately (1-10% in production)
  2. Add meaningful tags (user_id, request_id)
  3. Propagate context across all service boundaries
  4. Log exceptions in spans
  5. Use consistent naming for operations
  6. Monitor tracing overhead (<1% CPU impact)
  7. Set up alerts for trace errors
  8. Implement distributed context (baggage)
  9. Use span events for important milestones
  10. Document instrumentation standards

What it can do on your machine

Read from SKILL.md and the folder at commit 46891e7. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are python).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Distributed Tracing loads about 527 tokens when it runs, and up to ~2.5k if it reads all its reference files. Until then it costs about 66 tokens; SKILL.md has 174 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~66
When it runs · the whole SKILL.md, loaded when a task matches
~527
With references · SKILL.md plus every file in references/, read only if the agent opens them
~2.5k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from wshobson/agents at commit 46891e7, republished under its MIT licence (© wshobson). 174 words, ~527 tokens.

Download SKILL.mdSave it as .claude/skills/distributed-tracing/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
distributed-tracing
description
Implement distributed tracing with Jaeger and Tempo to track requests across microservices and identify performance bottlenecks. Use when debugging microservices, analyzing request flows, or implementing observability for distributed systems.

Distributed Tracing

Implement distributed tracing with Jaeger and Tempo for request flow visibility across microservices.

Purpose

Track requests across distributed systems to understand latency, dependencies, and failure points.

When to Use

  • Debug latency issues
  • Understand service dependencies
  • Identify bottlenecks
  • Trace error propagation
  • Analyze request paths

Detailed patterns and worked examples

Detailed pattern documentation lives in references/details.md. Read that file when the navigation tier above is insufficient.

Best Practices

  1. Sample appropriately (1-10% in production)
  2. Add meaningful tags (user_id, request_id)
  3. Propagate context across all service boundaries
  4. Log exceptions in spans
  5. Use consistent naming for operations
  6. Monitor tracing overhead (<1% CPU impact)
  7. Set up alerts for trace errors
  8. Implement distributed context (baggage)
  9. Use span events for important milestones
  10. Document instrumentation standards

Integration with Logging

Correlated Logs
python
import logging
from opentelemetry import trace

logger = logging.getLogger(__name__)

def process_request():
    span = trace.get_current_span()
    trace_id = span.get_span_context().trace_id

    logger.info(
        "Processing request",
        extra={"trace_id": format(trace_id, '032x')}
    )

Troubleshooting

No traces appearing:

  • Check collector endpoint
  • Verify network connectivity
  • Check sampling configuration
  • Review application logs

High latency overhead:

  • Reduce sampling rate
  • Use batch span processor
  • Check exporter configuration
  • prometheus-configuration - For metrics
  • grafana-dashboards - For visualization
  • slo-implementation - For latency SLOs

© wshobson, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file (references) in plugins/observability-monitoring/skills/distributed-tracing of wshobson/agents.

  • SKILL.md
  • references/details.md

Open the folder on GitHubat commit 46891e7

Used in 12 other repositories

We found 34 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 12 other GitHub owners. This page covers the copy in wshobson/agents, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Distributed Tracing next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Distributed Tracing compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Distributed Tracing this skillwshobson/agents40k12 repos~527Automated safety check: PassMIT
Add Metricmicrobus-io/fabric172—~1.5kAutomated safety check: PassApache-2.0
Service Mesh Expertaiskillstore/marketplace4307 repos~686Automated safety check: PassNone
Setting Up Distributed Tracingjeremylongshore/tons-of-skills-marketplace2.8k—~896Automated safety check: PassMIT
Spine Servicejeremylongshore/tons-of-skills-marketplace2.8k—~804Automated safety check: NotesMIT
KubeSphere ServiceMesh Managerkubesphere/kubesphere17k—~2.4kAutomated safety check: PassCustom licence

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Questions about Distributed Tracing

What does Distributed Tracing do?

Implement distributed tracing with Jaeger and Tempo to track requests across microservices and identify performance bottlenecks. Distributed Tracing is an agent skill from wshobson/agents. Implement distributed tracing with Jaeger and Tempo to track requests across microservices and identify performance bottlenecks.

When should I use Distributed Tracing?

Distributed Tracing fits situations like: debugging microservices; analyzing request flows; implementing observability for distributed systems.

How do I install Distributed Tracing in Claude Code?

Run `npx skills add wshobson/agents --skill distributed-tracing -a claude-code`. Or copy the skill folder (plugins/observability-monitoring/skills/distributed-tracing in wshobson/agents) into .claude/skills/distributed-tracing in your project. Claude Code loads it when a task matches its description.

How do I install Distributed Tracing in Codex?

Run `npx skills add wshobson/agents --skill distributed-tracing -a codex`. Or copy the skill folder (plugins/observability-monitoring/skills/distributed-tracing in wshobson/agents) into .agents/skills/distributed-tracing in your project. Codex loads it when a task matches its description.

Can I use Distributed Tracing in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add wshobson/agents --skill distributed-tracing -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/distributed-tracing, .gemini/skills/distributed-tracing, .github/skills/distributed-tracing and .opencode/skills/distributed-tracing in your project.

What does Distributed Tracing need to run?

SKILL.md names no scripts, command-line tools or credentials: Distributed Tracing is instructions for the agent only. Our summary lists: Python 3.

Does Distributed Tracing access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Distributed Tracing safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Distributed Tracing use?

Distributed Tracing is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Distributed Tracing use?

About 527 tokens (SKILL.md is roughly 2.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2k tokens, read only when the agent opens those files.

What are the alternatives to Distributed Tracing?

Skills that share tags, products or a category with Distributed Tracing: Add Metric (microbus-io/fabric, 172 stars), Service Mesh Expert (aiskillstore/marketplace, 430 stars), Setting Up Distributed Tracing (jeremylongshore/tons-of-skills-marketplace, 2.8k stars) and Spine Service (jeremylongshore/tons-of-skills-marketplace, 2.8k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Distributed Tracing?

wshobson (a GitHub user) maintains it in wshobson/agents, which has 40,305 GitHub stars. The repository holds 142 skills in this directory. The repository was last updated on October 5, 2026.

Source: wshobson/agents on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.