Diagnose pipeline failures in minutes, not hours
When a pipeline fails, paste the error log and get a plain-English diagnosis with the likely root cause, affected downstream systems, and a suggested fix. Helps you get from stack trace to next step fast.
Create a skill called "Pipeline Medic". When I paste an error log, stack trace, or failure notification from a data pipeline, analyze it and produce: (1) A one-sentence summary of what failed. (2) The root cause, categorized as: schema change, credential/auth issue, resource limit (memory/disk/timeout), data quality issue, code bug, or infrastructure problem. (3) The specific line or component that failed, with context. (4) A suggested fix with actual commands or code changes. (5) A list of likely downstream impacts (which dashboards or reports might be affected). (6) A stakeholder-friendly summary I can paste into Slack ("The daily revenue dashboard may show yesterday's numbers because..."). Support Airflow, dbt, Prefect, Dagster, Fivetran, and generic Python/bash pipeline logs.
Airflow task failures produce 500-line stack traces. dbt errors reference
model files three levels deep. The actual root cause is usually one thing —
a schema change, an expired credential, a resource limit — buried in noise.
This skill extracts the signal.
Describe a pipeline in English, get a working Airflow DAG
Skip the boilerplate. Describe your data pipeline in plain English and get a complete Airflow DAG with proper dependencies, error handling, retries, and alerting. Also debugs failing DAGs by analyzing task logs.
Know about stale data before your stakeholders do
Monitors your key tables for freshness, row counts, and schema changes on a schedule. Alerts you via Slack or Telegram before business hours when something looks off — so you're never blindsided by a stakeholder asking "why is the dashboard blank?"
Freeze first, sort later
A brokerage-account incident response checklist for suspicious access, account takeover concerns, and evidence capture when something looks wrong.
Local-first AI assistant that automates small daily tasks safely on your device
A personal, local-first AI assistant that automates small daily tasks—organizing files, setting reminders, and monitoring system events—without touching sensitive data or taking risky actions without your approval.