tracing-schema-generator
Generate distributed tracing schemas for OpenTelemetry with Jaeger/Zipkin integration
Best use case
tracing-schema-generator is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Generate distributed tracing schemas for OpenTelemetry with Jaeger/Zipkin integration
Teams using tracing-schema-generator should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/tracing-schema-generator/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How tracing-schema-generator Compares
| Feature / Agent | tracing-schema-generator | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Generate distributed tracing schemas for OpenTelemetry with Jaeger/Zipkin integration
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Tracing Schema Generator Skill
## Overview
Generates OpenTelemetry tracing schemas including span attribute definitions, trace context propagation, and Jaeger/Zipkin integration configurations.
## Capabilities
- OpenTelemetry tracing schemas
- Span attribute definitions
- Trace context propagation (W3C, B3)
- Jaeger integration
- Zipkin integration
- Baggage propagation
- Sampling strategy configuration
- Span naming conventions
## Target Processes
- observability-implementation
- microservices-decomposition
## Input Schema
```json
{
"type": "object",
"required": ["services"],
"properties": {
"services": {
"type": "array",
"items": {
"type": "object",
"properties": {
"name": { "type": "string" },
"operations": { "type": "array" },
"dependencies": { "type": "array" }
}
}
},
"propagation": {
"type": "string",
"enum": ["w3c", "b3", "jaeger"],
"default": "w3c"
},
"backend": {
"type": "string",
"enum": ["jaeger", "zipkin", "tempo", "xray"],
"default": "jaeger"
},
"options": {
"type": "object",
"properties": {
"samplingRate": {
"type": "number",
"default": 0.1
},
"samplingStrategy": {
"type": "string",
"enum": ["always_on", "always_off", "trace_id_ratio", "parent_based"],
"default": "trace_id_ratio"
},
"includeBaggage": {
"type": "boolean",
"default": true
},
"semanticConventions": {
"type": "string",
"enum": ["http", "db", "messaging", "rpc"],
"default": "http"
}
}
}
}
}
```
## Output Schema
```json
{
"type": "object",
"properties": {
"spanDefinitions": {
"type": "array",
"items": {
"type": "object",
"properties": {
"name": { "type": "string" },
"kind": { "type": "string" },
"attributes": { "type": "array" },
"events": { "type": "array" }
}
}
},
"propagationConfig": {
"type": "object"
},
"samplerConfig": {
"type": "object"
},
"exporterConfig": {
"type": "object",
"description": "Jaeger/Zipkin exporter configuration"
},
"instrumentation": {
"type": "object",
"description": "Auto-instrumentation configuration"
}
}
}
```
## Usage Example
```javascript
{
kind: 'skill',
skill: {
name: 'tracing-schema-generator',
context: {
services: [
{
name: 'order-service',
operations: ['createOrder', 'getOrder', 'updateOrder'],
dependencies: ['inventory-service', 'payment-service']
}
],
propagation: 'w3c',
backend: 'jaeger',
options: {
samplingRate: 0.1,
samplingStrategy: 'trace_id_ratio'
}
}
}
}
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