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Instrument an LLM app with OpenInference v1.0.0

Use this resource to add OpenInference tracing to an LLM application and prepare it for production

New

  • 508 downloads
  • 139 likes
  • 136 saves

Free

Install with the CLI

In a terminal, from the folder you want:

npx --yes palatekit@latest install llm-tracing-openinference

With no option, the skill goes to ~/.agents/skills/; add --agent claude-code (or codex, cursor…) to target an agent.

First time: connect the CLI with

npx --yes palatekit@latest login

The agent follows the skill's references to install Phoenix tracing in Python or TypeScript, instrument LLM calls, create custom spans and add the required attributes. It also covers annotations and deployment.

Mostly picked by

Updated November 2, 2026

Card for the “Instrument an LLM app with OpenInference” skill

Details

Works in
Install guides
Generates with
Your agent's model
Licence
Apache-2.0

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What you get

  • SKILL.md and README.md: overview, categories and working order
  • references/: attributes, automatic and manual instrumentation, annotations

Good fit for

  • You want to see every LLM call in Phoenix with its inputs and outputs
  • You are moving a working agent to production

Not for

    Tags

    • tracing
    • openinference
    • opentelemetry
    • observability

    About

    You say

    “Instrument my Python app with OpenAI and send the traces to a local Phoenix.”

    Card for the “Instrument an LLM app with OpenInference” skill

    Skill published by arize-ai under the Apache-2.0 license, delivered in its original version.

    Show more

    How to use it

    1. Install the skill in your agent's skills folder
    2. Ask your agent to add OpenInference tracing to an LLM application and prepare it for production
    3. Review and adjust the result

    Content preview

    Files

    • LICENSE3.7 KB
    • NOTICE-PALATEKIT.md0.5 KB
    • README.md0.8 KB
    • references/annotations-overview.md3.9 KB
    • references/annotations-python.md3.2 KB
    • references/annotations-typescript.md4.2 KB
    • references/fundamentals-flattening.md1.9 KB
    • references/fundamentals-overview.md1.9 KB
    • references/fundamentals-required-attributes.md2.7 KB
    • references/fundamentals-universal-attributes.md2.4 KB
    • references/instrumentation-atif-python.md9.3 KB
    • references/instrumentation-auto-python.md4.4 KB
    • references/instrumentation-auto-typescript.md4.6 KB
    • references/instrumentation-manual-python.md7 KB
    • references/instrumentation-manual-typescript.md8.4 KB
    • references/metadata-python.md1.9 KB
    • references/metadata-typescript.md1.1 KB
    • references/production-python.md2.2 KB
    • references/production-typescript.md4 KB
    • references/projects-python.md3.5 KB
    • references/projects-typescript.md4.8 KB
    • references/sessions-python.md2.4 KB
    • references/sessions-typescript.md6.9 KB
    • references/setup-python.md5 KB
    • references/setup-typescript.md6.9 KB
    • references/span-agent.md0.4 KB
    • references/span-chain.md1.3 KB
    • references/span-decision.md5.2 KB
    • references/span-embedding.md2.8 KB
    • references/span-evaluator.md1.7 KB
    • references/span-guardrail.md1.4 KB
    • references/span-llm.md4.7 KB
    • references/span-reranker.md3.3 KB
    • references/span-retriever.md3.5 KB
    • references/span-tool.md2.7 KB
    • SKILL.md6.7 KB

    Origin and licence

    Listed unmodified

    Author
    arize-ai
    Source
    github.com/arize-ai/phoenix/tree/2196d813a80586c7bd3a3b91a6092d6a3fabb10c/.agents/skills/phoenix-tracing
    Licence
    Apache-2.0

    Notice

    « phoenix-tracing » (arize-ai, Apache-2.0) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.

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