Apache DataFusion Python Bindings is a Python library connecting applications to DataFusion, an in-memory query engine built on Apache Arrow. It is for building Python data systems that query CSV, Parquet, and JSON data with SQL or DataFrames, optimize those queries, run Python code, and exchange data with other DataFrame libraries. The catalogue add-ons support development workflows around these Python bindings.
Borrowing it
Nothing to install: this file belongs to apache/datafusion-python. 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/apache/datafusion-python/main/AGENTS.mdgit clone --depth 1 https://github.com/apache/datafusion-pythonWrote 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/apache/datafusion-python/agents-md)<a href="https://agentmods.dev/instructions/apache/datafusion-python/agents-md"><img src="https://agentmods.dev/badge/instructions/apache/datafusion-python/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/apache/datafusion-python/agents-md"><img src="https://agentmods.dev/badge/instructions/apache/datafusion-python/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 | $0.02052 | $0.02052 |
| Opus 5.5 | $0.00821 | $0.00821 |
| Sonnet 5.5 | $0.00410 | $0.00410 |
| Haiku 4.5 | $0.00205 | $0.00205 |
Grade A, and why
datafusion-python 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 — 188 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Instructions for Contributors
This file is for agents working on the datafusion-python project (developing,
testing, reviewing). If you need to use the DataFusion DataFrame API (write
queries, build expressions, understand available functions), see the user-facing
skill at SKILL.md.
Skills
This project uses AI agent skills stored in .ai/skills/. Each skill is a directory containing a SKILL.md file with instructions for performing a specific task.
Skills follow the Agent Skills open standard. Each skill directory contains:
SKILL.md— The skill definition with YAML frontmatter (name, description, argument-hint) and detailed instructions.- Additional supporting files as needed.
To discover what skills are available, list .ai/skills/ and read each
SKILL.md. The frontmatter name and description fields summarize the
skill's purpose. Some descriptions begin with TRIGGER —; those are not tasks
to run on request but conventions to read before writing code that meets the
stated condition.
FFI Capsule Protocol
The __datafusion_*__ capsule getters are one protocol with a settled
convention. Before adding or changing one, read
.ai/skills/ffi-capsule-protocol/SKILL.md.
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 Changed · +41 lines · +470 tokens per session aed176f11076
- 1mo ago Changed · +34 lines · +431 tokens per session 75411003f033
- 2mo ago First seen · 113 lines · 1,151 tokens per session scan A bba09e576695
datafusion-python AGENTS.md is an instructions file published in the GitHub repository apache/datafusion-python (610 stars, last pushed 4d ago), licensed Apache-2.0. It adds 2,052 tokens to every session, about $0.0082 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.
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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.
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Copilot instructions for microsoft/vscode, covering vs code copilot instructions, project overview, root folders, core architecture (src/ folder) and built-in extensions (extensions/ folder).
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AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.