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/nevaberry/nevaberry-plugins/airflow-knowledge-patchnpx skills add Nevaberry/nevaberry-plugins --skill airflow-knowledge-patchgit clone --depth 1 https://github.com/Nevaberry/nevaberry-pluginsWhat 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 | $0.00010 | $0.02012 |
| Opus 5 | $0.00005 | $0.01006 |
| Sonnet 5 | $0.00002 | $0.00402 |
| Haiku 4.5 | $0.00001 | $0.00201 |
Grade A, and why
airflow-knowledge-patch 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 3d 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 — 198 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Apache Airflow Knowledge Patch
Use this skill when authoring, upgrading, integrating, or operating Apache Airflow. Start with the quick guidance below, then open the topic reference that matches the work.
Reference index
| Reference | Topics |
|---|---|
| upgrade-and-compatibility.md | Upgrade sequencing, stable interfaces, removed APIs, serialization, runtimes, pandas, and Dag bundles |
| task-authoring-and-execution.md | Task context, XCom, callbacks, operators, HITL, state stores, retry policy, and durable execution |
| scheduling-assets-and-deadlines.md | Scheduling defaults, Dag versions, backfills, Assets, partitions, clearing, Deadline Alerts, and teams |
| api-cli-and-ui.md | Authentication, REST semantics, airflowctl, CLI changes, UI streams, and sensitive configuration |
| operations-logging-and-extensions.md | Services, plugins, deployment, security, remote logs, metrics, and tracing |
Upgrade first principles
Author against airflow.sdk
Use the semver-governed SDK for Dag authoring and task execution:
from airflow.sdk import Asset, DAG, dag, get_current_context, task
Move Dataset* names to their Asset* equivalents and airflow.io.* imports to airflow.sdk.io.*. Treat unlisted Python modules, metadata ORM/schema details, and Web UI HTML as internal.
Do not subclass built-in executors as a compatibility contract. For built-in operators, rely on documented parameters and behavior, not methods or class structure.
Run a staged preflight
Before the core upgrade:
- Move to a recent Airflow 2.x release, at least 2.7.
- Back up the metadata database and clean it if appropriate.
- Make Dag parsing and reserialization error-free.
- Run Ruff Airflow checks and migrate provider imports.
- Diagnose configuration changes, then migrate the database.
What ships with it
6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 3d ago First seen · 198 lines · 10 tokens per session scan A 79f9eb2205de
airflow-knowledge-patch is a skill published in the GitHub repository Nevaberry/nevaberry-plugins (24 stars, last pushed 7d ago), licensed MIT. It adds 10 tokens to every session and 2,012 once invoked, about $0.0001 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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