OpenInference is a set of conventions and instrumentation plugins for tracing AI applications with OpenTelemetry. It helps developers record language-model calls, retrieval from vector stores, and external tool use for analysis in compatible observability backends. The catalogue entries support instrumentation and use of these tracing conventions.
Borrowing it
Nothing to install: this file belongs to Arize-ai/openinference. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Arize-ai/openinference/main/AGENTS.mdgit clone --depth 1 https://github.com/Arize-ai/openinferenceWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/arize-ai/openinference/agents-md)<a href="https://agentmods.dev/instructions/arize-ai/openinference/agents-md"><img src="https://agentmods.dev/badge/instructions/arize-ai/openinference/agents-md/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/instructions/arize-ai/openinference/agents-md"><img src="https://agentmods.dev/badge/instructions/arize-ai/openinference/agents-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.01064 | $0.01064 |
| Opus 5.5 | $0.00426 | $0.00426 |
| Sonnet 5.5 | $0.00213 | $0.00213 |
| Haiku 4.5 | $0.00106 | $0.00106 |
Grade A, and why
openinference AGENTS.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 177 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md
This file provides guidance to Claude Code when working with this repository.
Repository Overview
OpenInference is a multi-language monorepo providing OpenTelemetry-based instrumentation for AI/ML applications:
- Python: Instrumentation for OpenAI, LangChain, LlamaIndex, DSPy, etc.
- JavaScript/TypeScript: Node.js instrumentations with pnpm workspaces
- Java: Instrumentation for LangChain4j and Spring AI
- Specification: OpenInference semantic conventions in
spec/
Repository Structure
.
├── python/ # Python packages and instrumentations
│ ├── instrumentation/ # Individual instrumentor packages
│ ├── openinference-instrumentation/
│ └── openinference-semantic-conventions/
├── js/ # JavaScript/TypeScript workspace
│ ├── packages/ # pnpm workspace packages
│ └── examples/
├── java/ # Java packages
│ ├── instrumentation/
│ ├── openinference-instrumentation/
│ └── openinference-semantic-conventions/
├── spec/ # OpenInference specification
└── scripts/ # Repository automation scripts
Essential Commands by Language
Python
Package Management:
# Install development dependencies
pip install -r python/dev-requirements.txt
# Install tox-uv for testing automation
pip install tox-uv==1.11.2
# Compose namespace package
tox run -e add_symlinks
# Install in editable mode
pip install -e python/openinference-instrumentation
Testing and Quality:
# Run all CI checks in parallel
tox run-parallel
# Run tests for specific package (e.g., openai)
tox run -e test-openai
# Run linting and formatting
tox run -e ruff-openai
# Run type checking
tox run -e mypy-openai
# Run all checks for a package
tox run -e ruff-mypy-test-openai
Key Tools:
- tox for automation
- ruff for formatting and linting
- mypy for type checking
JavaScript/TypeScript
See js/CLAUDE.md for detailed JavaScript-specific guidance.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 177 lines · 1,064 tokens per session scan A 1d7143ee3f8c
openinference AGENTS.md is an instructions file published in the GitHub repository Arize-ai/openinference (1,291 stars, last pushed today), licensed Apache-2.0. It adds 1,064 tokens to every session, about $0.0043 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other instructions, from other repositories
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, cache eligibility and rollout and applying the notice (cutover).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
vscode copilot-instructions.md
Copilot instructions for microsoft/vscode, covering vs code copilot instructions, project overview, root folders, core architecture (src/ folder) and built-in extensions (extensions/ folder).
vscode model-prompts.instructions.md
Model-specific prompt authoring and registry guidelines.