Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/arize-ai/openinference/python-code-reviewernpx skills add Arize-ai/openinference --skill python-code-reviewergit clone --depth 1 https://github.com/Arize-ai/openinferenceWhat 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 | $0.00100 | $0.03346 |
| Opus 5 | $0.00050 | $0.01673 |
| Sonnet 5 | $0.00020 | $0.00669 |
| Haiku 4.5 | $0.00010 | $0.00335 |
Grade A, and why
python-code-reviewer 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 yesterday.
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 — 366 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Python Code Reviewer for OpenInference Instrumentors
Review a Python OpenInference instrumentation package against the project's established patterns and conventions. This is a checklist-driven review — go through each section, report findings with file paths and line numbers, and surface issues organized by severity.
Workflow
Step 1: Identify the package to review
- Ask the user which instrumentor to review if not already clear from context
- The package lives under
python/instrumentation/openinference-instrumentation-<name>/ - Read the key files:
__init__.py,_wrappers.py(or equivalent),pyproject.toml, and the fulltests/directory
Step 2: Pull the instrumented library source and use it as ground truth
OpenInference instrumentors work by monkey-patching functions in the library they instrument. All correctness judgments — whether wrappers target the right methods, handle the right signatures, process the right data structures, and cover the right edge cases — must be verified against the actual library source code. Do NOT make assumptions about how the instrumented library works.
Note: The tox env name
<pkg>and the library's Python import path<library>often differ. For example,google_genaiis the tox env name but the library installs asgoogle/genai/in site-packages. Checktest-requirements.txtorpyproject.tomlto find the actual library package name.
- Set up the tox environment to install the pinned library version. Look up the
tox envlist in
python/tox.inito find the correct env name (use the highest Python version available, e.g.,py314,py313):
(cd python && uvx --with tox-uv tox run -e <pyVER>-ci-<pkg> -- --co -q-- --co -qtells pytest to collect without running, which triggers the install.) If the.toxenv already exists, skip this step. If tox setup fails (missing Python version, dependency conflicts), fall back topip install <library>in a temporary venv to unblock the review.
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.
- yesterday First seen · 366 lines · 100 tokens per session scan A d7083cc2e6bf
python-code-reviewer is a skill published in the GitHub repository Arize-ai/openinference (1,186 stars, last pushed 2d ago), licensed Apache-2.0. It adds 100 tokens to every session and 3,346 once invoked, about $0.0005 per session on Opus 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.
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