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 instructions/apache/datafusion-python/agents-mdgit clone --depth 1 https://github.com/apache/datafusion-pythonWhat 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 | $0.01151 | $0.01151 |
| Opus 5 | $0.00575 | $0.00575 |
| Sonnet 5 | $0.00230 | $0.00230 |
| Haiku 4.5 | $0.00115 | $0.00115 |
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 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 — 113 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.
- yesterday 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 (598 stars, last pushed 2d ago), licensed Apache-2.0. It adds 1,151 tokens to every session, about $0.0058 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.
Other instructions, from other repositories
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
buildNext
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
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, applying the notice (cutover) and fallback chain (never fail the build).
spec-kit AGENTS.md
Instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.
langchain 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.