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/astronomer/agents/debugging-dagsnpx skills add astronomer/agents --skill debugging-dagsgit clone --depth 1 https://github.com/astronomer/agentsWhat 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 | $0.00111 | $0.01802 |
| Opus 5 | $0.00056 | $0.00901 |
| Sonnet 5 | $0.00022 | $0.00360 |
| Haiku 4.5 | $0.00011 | $0.00180 |
Grade A, and why
debugging-dags scanned grade A with 1 finding 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 2d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s https://pypi.org/pypi/<pkg>/json | jq '.releases | to_entries | map({version: .key, uploaded: .value[0].upload_time}) | sort_by(.uploaded) | reverse | .[:5]' How it starts
The opening of the file, as written. The whole thing — 129 lines — stays where its author put it; the contents beside it link to each section on GitHub.
DAG Diagnosis
You are a data engineer debugging a failed Airflow DAG. Follow this systematic approach to identify the root cause and provide actionable remediation.
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.
Step 1: Identify the Failure
If a specific DAG was mentioned:
- Run
af runs diagnose <dag_id> <dag_run_id>(if run_id is provided) - If no run_id specified, run
af dags statsto find recent failures
If no DAG was specified:
- Run
af healthto find recent failures across all DAGs - Check for import errors with
af dags errors - Show DAGs with recent failures
- Ask which DAG to investigate further
Step 2: Get the Error Details
Once you have identified a failed task:
- Get task logs using
af tasks logs <dag_id> <dag_run_id> <task_id> - Look for the actual exception - scroll past the Airflow boilerplate to find the real error
- Categorize the failure type:
- Data issue: Missing data, schema change, null values, constraint violation
- Code issue: Bug, syntax error, import failure, type error
- Infrastructure issue: Connection timeout, resource exhaustion, permission denied
- Dependency issue: Upstream failure, external API down, rate limiting
Step 3: Check Context
Gather additional context to understand WHY this happened:
- Recent changes: Was there a code deploy? Check git history if available
- Package version changes: Was a package upgraded — in the image, in a venv-style operator, or at the index? See Package version changes below.
- Data volume: Did data volume spike? Run a quick count on source tables
- Upstream health: Did upstream tasks succeed but produce unexpected data?
- Historical pattern: Is this a recurring failure? Check if same task failed before
- Timing: Did this fail at an unusual time? (resource contention, maintenance windows)
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.
- 2d ago First seen · 129 lines · 111 tokens per session scan A 72e6f2caf8cf
debugging-dags is a skill published in the GitHub repository astronomer/agents (432 stars, last pushed 15d ago), licensed Apache-2.0. It adds 111 tokens to every session and 1,802 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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