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 testing-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/testing-dags)<a href="https://agentmods.dev/skills/astronomer/agents/testing-dags"><img src="https://agentmods.dev/badge/skills/astronomer/agents/testing-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/testing-dags"><img src="https://agentmods.dev/badge/skills/astronomer/agents/testing-dags.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- 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 | $0.00077 | $0.02580 |
| Opus 5.5 | $0.00031 | $0.01032 |
| Sonnet 5.5 | $0.00015 | $0.00516 |
| Haiku 4.5 | $0.00008 | $0.00258 |
Grade A, and why
testing-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.
How it starts
The opening of the file, as written. The whole thing — 414 lines — stays where its author put it; the contents beside it link to each section on GitHub.
DAG Testing Skill
Use af commands to test, debug, and fix DAGs in iterative cycles.
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.
Quick Validation with Astro CLI
If the user has the Astro CLI available, these commands provide fast feedback without needing a running Airflow instance:
# Parse DAGs to catch import errors, syntax issues, and DAG-level problems
astro dev parse
# Run pytest against DAGs (runs tests in tests/ directory)
astro dev pytest
Use these for quick validation during development. For full end-to-end testing against a live Airflow instance, continue to the trigger-and-wait workflow below.
FIRST ACTION: Just Trigger the DAG
When the user asks to test a DAG, your FIRST AND ONLY action should be:
af runs trigger-wait <dag_id>
DO NOT:
- Call
af dags listfirst - Call
af dags getfirst - Call
af dags errorsfirst - Use
greporlsor any other bash command - Do any "pre-flight checks"
Just trigger the DAG. If it fails, THEN debug.
Testing Workflow Overview
┌─────────────────────────────────────┐
│ 1. TRIGGER AND WAIT │
│ Run DAG, wait for completion │
└─────────────────────────────────────┘
↓
┌───────┴───────┐
↓ ↓
┌─────────┐ ┌──────────┐
│ SUCCESS │ │ FAILED │
│ Done! │ │ Debug... │
└─────────┘ └──────────┘
↓
┌─────────────────────────────────────┐
│ 2. DEBUG (only if failed) │
│ Get logs, identify root cause │
└─────────────────────────────────────┘
↓
┌─────────────────────────────────────┐
│ 3. FIX AND RETEST │
│ Apply fix, restart from step 1 │
└─────────────────────────────────────┘
Philosophy: Try first, debug on failure. Don't waste time on pre-flight checks — just run the DAG and diagnose if something goes wrong.
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 · 414 lines · 77 tokens per session scan A 5c03dde0d39b
testing-dags is a skill published in the GitHub repository astronomer/agents (453 stars, last pushed 3d ago), licensed Apache-2.0. It adds 77 tokens to every session and 2,580 once invoked, about $0.0003 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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