Quick Start
You can add these skills to your local environment in seconds:Available skills
| Skill | Best For | Install command |
|---|---|---|
netra-best-practices | End-to-end instrumentation, observability, and evaluation. | npx skills add KeyValueSoftwareSystems/netra-skills --skill netra-best-practices |
netra-mcp-usage | MCP trace debugging focused on query and retrieval operations. | npx skills add KeyValueSoftwareSystems/netra-skills --skill netra-mcp-usage |
When To Use
- You want one workflow that replaces separate setup and instrumentation skills.
- You need traceability from request context to span-level debugging.
- You need precise, schema-correct inputs for Netra MCP query and retrieval tools.
- You need repeatable quality validation with evaluations and simulations.
- You need production-safe troubleshooting guidance.
Coverage
- Setup and Baseline: Initialize the SDK correctly for Python (FastAPI/OpenAI) and TypeScript (Express/OpenAI).
- Context Tracking: Implement request identity (
user_id,session_id,tenant_id) and conversation logging. - Trace Debugging: Execute precise
query_tracesandget_trace_by_idcalls with correct schemas, sorting, and pagination. - Instrumentation Strategy: Choose between auto-instrumentation, decorators (
@workflow,@agent,@task), and manual spans. - Advanced Observability: Implement usage/cost tracking, action records, and OpenTelemetry custom metrics.
- Evaluation: Set up single-turn evaluations and multi-turn simulations with representative datasets.
- Trace Analysis: Use Netra MCP tools (
netra_query_traces,netra_get_trace_by_id) to debug regressions.
Related Resources
- Netra MCP - Connect Netra’s remote MCP server to your editor
- Tracing Quick Start - Fastest path to visible traces
- Evaluation Quick Start - Build datasets and evaluators
- Simulation Quick Start - Test multi-turn behavior
- SDK Overview - Core SDK concepts
