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/checking-freshnessnpx skills add astronomer/agents --skill checking-freshnessgit 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 | $0.00044 | $0.00827 |
| Opus 5 | $0.00022 | $0.00413 |
| Sonnet 5 | $0.00009 | $0.00165 |
| Haiku 4.5 | $0.00004 | $0.00083 |
Grade A, and why
checking-freshness 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 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.
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
1 near-identical copy found in the catalogue:
- checking-freshness — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Data Freshness Check
Quickly determine if data is fresh enough to use.
Freshness Check Process
For each table to check:
1. Find the Timestamp Column
Look for columns that indicate when data was loaded or updated:
_loaded_at,_updated_at,_created_at(common ETL patterns)updated_at,created_at,modified_at(application timestamps)load_date,etl_timestamp,ingestion_timedate,event_date,transaction_date(business dates)
Query INFORMATION_SCHEMA.COLUMNS if you need to see column names.
2. Query Last Update Time
SELECT
MAX(<timestamp_column>) as last_update,
CURRENT_TIMESTAMP() as current_time,
TIMESTAMPDIFF('hour', MAX(<timestamp_column>), CURRENT_TIMESTAMP()) as hours_ago,
TIMESTAMPDIFF('minute', MAX(<timestamp_column>), CURRENT_TIMESTAMP()) as minutes_ago
FROM <table>
3. Check Row Counts by Time
For tables with regular updates, check recent activity:
SELECT
DATE_TRUNC('day', <timestamp_column>) as day,
COUNT(*) as row_count
FROM <table>
WHERE <timestamp_column> >= DATEADD('day', -7, CURRENT_DATE())
GROUP BY 1
ORDER BY 1 DESC
Freshness Status
Report status using this scale:
| Status | Age | Meaning |
|---|---|---|
| Fresh | < 4 hours | Data is current |
| Stale | 4-24 hours | May be outdated, check if expected |
| Very Stale | > 24 hours | Likely a problem unless batch job |
| Unknown | No timestamp | Can't determine freshness |
If Data is Stale
Check Airflow for the source pipeline:
-
Find the DAG: Which DAG populates this table? Use
af dags listand look for matching names. -
Check DAG status:
- Is the DAG paused? Use
af dags get <dag_id> - Did the last run fail? Use
af dags stats - Is a run currently in progress?
- Is the DAG paused? Use
-
Diagnose if needed: If the DAG failed, use the debugging-dags skill to investigate.
On Astro
If you're running on Astro, you can also:
- DAG history in the Astro UI: Check the deployment's DAG run history for a visual timeline of recent runs and their outcomes
- Astro alerts for SLA monitoring: Configure alerts to get notified when DAGs miss their expected completion windows, catching staleness before users report it
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 · 110 lines · 44 tokens per session scan A 48ac4e767dc6
checking-freshness is a skill published in the GitHub repository astronomer/agents (432 stars, last pushed 15d ago), licensed Apache-2.0. It adds 44 tokens to every session and 827 once invoked, about $0.0002 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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