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 skills add astronomer/agents --skill authoring-dagsgit clone --depth 1 https://github.com/astronomer/agentsWrote 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/astronomer/agents/authoring-dags)<a href="https://agentmods.dev/skills/astronomer/agents/authoring-dags"><img src="https://agentmods.dev/badge/skills/astronomer/agents/authoring-dags/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/astronomer/agents/authoring-dags"><img src="https://agentmods.dev/badge/skills/astronomer/agents/authoring-dags.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Rogue Agent · line 3 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
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 | $0.00093 | $0.01596 |
| Opus 5.5 | $0.00037 | $0.00638 |
| Sonnet 5.5 | $0.00019 | $0.00319 |
| Haiku 4.5 | $0.00009 | $0.00160 |
Grade A, and why
authoring-dags 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.
Copies of this mod
2 near-identical copies found in the catalogue:
- authoring-dags — 91% identical, 23 lines differ
- authoring-dags — 91% identical, 10 lines differ
How it starts
The opening of the file, as written. The whole thing — 229 lines — stays where its author put it; the contents beside it link to each section on GitHub.
DAG Authoring Skill
This skill guides you through creating and validating Airflow DAGs using best practices and af CLI commands.
For testing and debugging DAGs, see the testing-dags skill which covers the full test -> debug -> fix -> retest workflow.
Running the CLI
These commands assume af is on PATH. Run via astro otto to get it automatically, or install standalone with uv tool install astro-airflow-mcp.
Workflow Overview
+-----------------------------------------+
| 1. DISCOVER |
| Understand codebase & environment |
+-----------------------------------------+
|
+-----------------------------------------+
| 2. PLAN |
| Propose structure, get approval |
+-----------------------------------------+
|
+-----------------------------------------+
| 3. IMPLEMENT |
| Write DAG following patterns |
+-----------------------------------------+
|
+-----------------------------------------+
| 4. VALIDATE |
| Check import errors, warnings |
+-----------------------------------------+
|
+-----------------------------------------+
| 5. TEST (with user consent) |
| Trigger, monitor, check logs |
+-----------------------------------------+
|
+-----------------------------------------+
| 6. ITERATE |
| Fix issues, re-validate |
+-----------------------------------------+
Phase 1: Discover
Before writing code, understand the context.
Explore the Codebase
Use file tools to find existing patterns:
Globfor**/dags/**/*.pyto find existing DAGsReadsimilar DAGs to understand conventions- Check
requirements.txtfor available packages
Query the Airflow Environment
Use af CLI commands to understand what's available:
What ships with it
1 file 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.
- 1mo ago First seen · 229 lines · 93 tokens per session scan A fdc043b57914
authoring-dags is a skill published in the GitHub repository astronomer/agents (454 stars, last pushed 9d ago), licensed Apache-2.0. It adds 93 tokens to every session and 1,596 once invoked, about $0.0004 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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