phoenix-tracing
OpenInference semantic conventions and instrumentation for Phoenix AI observability. Use when implementing LLM tracing, creating custom spans, or deploying to production.
npx skills add majiayu000/claude-skill-registry --skill phoenix-tracing --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Phoenix Tracing Comprehensive guide for instrumenting LLM applications with OpenInference tracing in Phoenix. Contains rule files covering setup, instrumentation, span types, and production deployment. ## When to Apply Reference these guidelines when: - Setting up Phoenix tracing (Python or TypeScript) - Creating custom spans for LLM operations - Adding attributes following OpenInference conventions - Deploying tracing to production - Querying and analyzing trace data ## Rule Categories | Priority | Category | Description | Prefix | | -------- | --------------- | ------------------------------ | -------------------------- | | 1 | Setup | Installation and configuration | `setup-*` | | 2 | Instrumentation | Auto and manual tracing | `instrumentation-*` | | 3 | Span Types | 9 span kinds with attributes | `span-*` | | 4 | Organization | Projects and sessions | `projects-*`, `sessions-*` | | 5 | Enrichment | Custom metadata | `metadata-*` | | 6 | Production | Batch processing, masking | `production-*` | | 7 | Feedback | Annotations and evaluation | `annotations-*` | ## Quick Reference ### 1. Setup (START HERE) - `setup-python` - Install arize-phoenix-otel, configure endpoint - `setup-
- When to Apply
- Rule Categories
- Quick Reference
- 1. Setup (START HERE)
- 2. Instrumentation
- 3. Span Types (with full attribute schemas)
- 4. Organization
- 5. Enrichment
- 6. Production (CRITICAL)
- 7. Feedback
- Reference Files
- Common Attributes
- Common Workflows
- How to Use
ls rules/span-* # Span type specifications ls rules/*-python.md # Python guides ls rules/*-typescript.md # TypeScript guides
What does the phoenix-tracing skill do?
OpenInference semantic conventions and instrumentation for Phoenix AI observability. Use when implementing LLM tracing, creating custom spans, or deploying to production.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill phoenix-tracing --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.