distributed-tracing
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.
Install with Tessl CLI
npx tessl i github:wshobson/agents --skill distributed-tracing89
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Discovery
100%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is a well-crafted skill description that excels across all dimensions. It uses third person voice, lists specific tools and actions, includes natural trigger terms that users would actually say, and has an explicit 'Use when...' clause with clear trigger scenarios. The combination of specific technologies (Jaeger, Tempo) with domain context (microservices, observability) makes it highly distinctive.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'implement distributed tracing', 'track requests across microservices', 'identify performance bottlenecks'. Names specific tools (Jaeger, Tempo) and concrete use cases. | 3 / 3 |
Completeness | Clearly answers both what ('implement distributed tracing with Jaeger and Tempo to track requests and identify bottlenecks') AND when ('Use when debugging microservices, analyzing request flows, or implementing observability'). | 3 / 3 |
Trigger Term Quality | Includes natural keywords users would say: 'distributed tracing', 'Jaeger', 'Tempo', 'microservices', 'request flows', 'observability', 'performance bottlenecks', 'debugging'. Good coverage of domain-specific terms. | 3 / 3 |
Distinctiveness Conflict Risk | Clear niche with distinct triggers - specifically targets distributed tracing with named tools (Jaeger, Tempo). Unlikely to conflict with general debugging or monitoring skills due to specific technology focus. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
72%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a comprehensive distributed tracing skill with excellent actionability through complete, executable code examples across multiple languages and deployment configurations. The main weaknesses are some unnecessary conceptual explanations that Claude already knows and a lack of explicit validation workflows to verify tracing is working correctly after setup.
Suggestions
Remove or significantly condense the 'Distributed Tracing Concepts' section - Claude understands traces, spans, and context propagation
Add an explicit validation workflow after setup: e.g., '1. Deploy Jaeger 2. Send test request 3. Verify trace appears in UI at http://localhost:16686 4. If no trace, check collector logs'
Add a quick verification command or script to confirm the tracing pipeline is working end-to-end
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill includes some unnecessary explanations (e.g., the 'Distributed Tracing Concepts' section explains basic concepts Claude already knows like what traces and spans are). The code examples are valuable but the document could be tightened by removing conceptual explanations. | 2 / 3 |
Actionability | Provides fully executable code examples across multiple languages (Python, Node.js, Go), complete Kubernetes manifests, Docker Compose configurations, and specific Jaeger queries. All examples are copy-paste ready with proper imports and configuration. | 3 / 3 |
Workflow Clarity | While individual setup steps are clear, there's no explicit validation workflow for verifying tracing is working correctly. The troubleshooting section exists but lacks a structured 'deploy -> verify -> debug' sequence with checkpoints to confirm traces are being collected. | 2 / 3 |
Progressive Disclosure | Well-organized with clear sections, appropriate references to external files (references/jaeger-setup.md, references/instrumentation.md, assets/jaeger-config.yaml.template), and related skills linked at the end. Content is appropriately split between overview and detailed references. | 3 / 3 |
Total | 10 / 12 Passed |
Validation
100%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 11 / 11 Passed
Validation for skill structure
No warnings or errors.
- Reviewed
Table of Contents
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