Apache Airflow is a platform for defining, scheduling, and monitoring workflows as code, with a scheduler assigning dependent tasks to workers. Teams use it to orchestrate automated data and software pipelines and inspect their progress through a user interface. Its catalogue skills and instructions help agents work with Airflow.
Borrowing it
Nothing to install: this file belongs to apache/airflow. 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/airflow/main/AGENTS.mdgit clone --depth 1 https://github.com/apache/airflowWrote 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/airflow/agents-md)<a href="https://agentmods.dev/instructions/apache/airflow/agents-md"><img src="https://agentmods.dev/badge/instructions/apache/airflow/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/airflow/agents-md"><img src="https://agentmods.dev/badge/instructions/apache/airflow/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 | $0.05396 | $0.05396 |
| Opus 5.5 | $0.02158 | $0.02158 |
| Sonnet 5.5 | $0.01079 | $0.01079 |
| Haiku 4.5 | $0.00540 | $0.00540 |
Grade A, and why
airflow 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 9d 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 — 254 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS instructions
Naming
Write Dag (title case) in all prose. Keep the all-caps or lowercase spelling only when reproducing a literal code token — never rewrite these, even inside fenced code blocks:
- Python: the SDK class
DAG(from airflow.sdk import DAG,dag = DAG("my_dag", ...)); identifiers likedag_id,dag,my_dag. - CLI:
airflow dags list,airflow dags test, etc. - Paths and config keys:
dag_processing/,dagprocessor,get_dag, etc. - Anti-pattern quotes that show the wrong form to teach the rule itself
(e.g.,
Use "DAG" — always write "Dag").
Don't spell out Directed Acyclic Graph except for historical context.
Environment Setup
- Install prek:
uv tool install prek - Enable commit hooks:
prek install - Install breeze shim (one-time, per machine):
scripts/tools/setup_breeze— installs~/.local/bin/breezethat runs breeze viauv run --lockedfrom the current git worktree'sdev/breeze, with dependencies pinned bydev/breeze/uv.lock(so each worktree, including ephemeral agent worktrees, gets its own breeze tied to its sources). See ADR 0017. - Never run pytest, python, or airflow commands directly on the host — always use
breeze. The only exception is theuv run --project <PROJECT> ...commands listed below, run against the workspace sources. - If a step needs
breezeand it cannot run (Docker missing, or its Docker calls refused by a sandbox or socket proxy), stop and tell the user which call failed. Do not build a substitute host environment instead, such as a virtualenv with a released Airflow version. - Place temporary scripts in
dev/(mounted as/opt/airflow/dev/inside Breeze).
Commands
<PROJECT> is folder where pyproject.toml of the package you want to test is located. For example, airflow-core or providers/amazon.
<target_branch> is the branch the PR will be merged into — usually main, but could be v3-1-test when creating a PR for the 3.1 branch.
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.
- 9d ago Changed · +2 lines · +130 tokens per session b59aa74425eb
- 19d ago Changed · -23 tokens per session 6a3c762f810a
- 1mo ago Changed · +1 lines · +54 tokens per session c1d589f742d9
- 1mo ago Changed · +4 lines · +73 tokens per session 167cd246efda
- 1mo ago Changed · +7 lines 95a748605b57
- 1mo ago Changed · -298 lines · -3,442 tokens per session 701b7265c785
- 1mo ago Changed · +2 tokens per session a07d140f253e
- 1mo ago Changed · +14 tokens per session 46773701753d
- 1mo ago Changed · +5 lines · -2 tokens per session 10c0e828b9be
- 2mo ago First seen · 533 lines · 8,590 tokens per session scan A be50de1e7a20
airflow AGENTS.md is an instructions file published in the GitHub repository apache/airflow (47,377 stars, last pushed yesterday), licensed Apache-2.0. It adds 5,396 tokens to every session, about $0.0216 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.
airflow AGENTS.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| airflow AGENTS.mdapache/airflow | Instructions file | 47k | yesterday | Apache-2.0 | A | 5,396 | Claude Code, Codex, OpenCode |
| vscode buildNext.instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 9,719 | GitHub Copilot |
| next.js AGENTS.mdvercel/next.js | Instructions file | 143k | today | MIT | A | 7,461 | Codex, OpenCode |
| vscode oss-third-party-notices.instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 5,516 | GitHub Copilot |
| langchain AGENTS.mdlangchain-ai/langchain | Instructions file | 149k | today | MIT | A | 4,680 | Codex, OpenCode |
| vscode copilot-instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 3,093 | GitHub Copilot |
| deepseek-harness AGENTS.mddeepseek-ai/deepseek-harness | Instructions file | 274k | 2d ago | MIT | A | 4,313 | Codex, OpenCode |