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/.ai/skills/check-upstream/SKILL.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/skills/apache/datafusion-python/check-upstream)<a href="https://agentmods.dev/skills/apache/datafusion-python/check-upstream"><img src="https://agentmods.dev/badge/skills/apache/datafusion-python/check-upstream/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/skills/apache/datafusion-python/check-upstream"><img src="https://agentmods.dev/badge/skills/apache/datafusion-python/check-upstream.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00000 | $0.05705 |
| Opus 5.5 | $0.00000 | $0.02282 |
| Sonnet 5.5 | $0.00000 | $0.01141 |
| Haiku 4.5 | $0.00000 | $0.00571 |
Grade A, and why
check-upstream 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 25d 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 — 479 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Check Upstream DataFusion Feature Coverage
You are auditing the datafusion-python project to find features from the upstream Apache DataFusion Rust library that are not yet exposed in this Python binding project. Your goal is to identify gaps and, if asked, implement the missing bindings.
IMPORTANT: The Python API is the source of truth for coverage. A function or method is considered "exposed" if it exists in the Python API (e.g., python/datafusion/functions.py), even if there is no corresponding entry in the Rust bindings. Many upstream functions are aliases of other functions — the Python layer can expose these aliases by calling a different underlying Rust binding. Do NOT report a function as missing if it appears in the Python __all__ list and has a working implementation, regardless of whether a matching #[pyfunction] exists in Rust.
IMPORTANT: audit the total upstream surface, not the delta since the last pin. Gaps accumulate across syncs. A patch-release bump with a "bug fixes only" changelog does not mean there is nothing to find — pre-existing gaps from earlier majors still need to be surfaced. Always run the full comparison.
Compile-Signal Triggers
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.
- 25d ago Changed · +1 lines f8185ce7f6da
- 2mo ago First seen · 478 lines · 0 tokens per session scan A 70d853ec61d9
check-upstream is a skill published in the GitHub repository apache/datafusion-python (610 stars, last pushed 4d ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 5,705 tokens. 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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python-review-checklist
Deterministic Python review checklist shipped with the CAO skills-lifecycle example.
plankton-code-quality
Write-time code quality enforcement using Plankton — auto-formatting, linting, and Claude-powered fixes on every file edit via hooks.
best-practices
Language-specific best practices, code quality standards, and framework detection rules. Use when executing refactoring workflows, applying code quality rules, detecting frameworks, or checking language-specific patterns for TypeScript, Python, Go, Swift, or React.
code-review-python
Reviews Python boundaries, typing, error handling, tests, dependencies, and supported-version idioms against the target project's contracts and active tools. Loaded by dh:code-reviewer for Python source; uses Python-engineering standards when available and retains standalone checks otherwise.
python-services
Python patterns for CLI tools, async parallelism, and backend services. Use when building CLI apps, async/parallel Python, FastAPI services, background jobs, or configuring Python project tooling (uv, ruff, ty).