data-catchall

Name: data-catchall
Author: Chipagosfinest

18stars6forks

How to install data-catchall?

chipagosfinest/enterprise-team/data-catchall

$npx -y skills add Chipagosfinest/enterprise-team --skill data-catchall

Installs into the current project.

Summary

Routes data requests to the correct specialist based on task type: pipelines, analytics, machine learning, or quality assurance. Covers ETL, warehousing, dashboards, ML models, and test automation. Triggers: data pipeline, etl, data warehouse, analytics, dashboard, metrics, kpi,

Files · 1

View on GitHub

SKILL.md

1	# Data Department
2
3	Routes data work to the appropriate specialist role.
4
5	## Routing Targets
6
7	\| Role \| Handles \|
8	\|---\|---\|
9	\| data-engineer \| ETL pipelines, data warehouses, Airflow, dbt, Spark, data infrastructure \|
10	\| data-analyst \| Dashboards, BI reports, SQL queries, KPIs, metrics, data exploration \|
11	\| data-scientist \| ML models, statistical analysis, predictive analytics, experiments \|
12	\| qa-engineer \| Test automation, CI/CD testing, data quality validation, regression testing \|
13
14	## Examples
15
16	- "Build an ETL pipeline to sync Stripe data to our warehouse" -> data-engineer
17	- "Create a dashboard showing monthly revenue by product" -> data-analyst
18	- "Train a churn prediction model on our user data" -> data-scientist
19	- "Set up automated data quality checks for the pipeline" -> qa-engineer
20	- "Migrate our data warehouse from Redshift to BigQuery" -> data-engineer
21	- "Analyze conversion funnel drop-off rates" -> data-analyst
22
23	## Workflow
24
25	1. Identify whether the request is about data infrastructure, analysis, modeling, or testing.
26	2. For requests spanning multiple areas (e.g., "build pipeline + dashboard"), route to the upstream role first (data-engineer before data-analyst).
27	3. For ambiguous data requests, default to data-analyst.
28	4. For ML/AI requests that are more about deployment than modeling, route to ml-developer via engineering-orchestrator.

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data-catchall

18stars6forks

View on GitHub

How to install data-catchall?

chipagosfinest/enterprise-team/data-catchall

$npx -y skills add Chipagosfinest/enterprise-team --skill data-catchall

Installs into the current project.

Summary

Files · 1

View on GitHub

SKILL.md

1	# Data Department
2
3	Routes data work to the appropriate specialist role.
4
5	## Routing Targets
6
7	\| Role \| Handles \|
8	\|---\|---\|
9	\| data-engineer \| ETL pipelines, data warehouses, Airflow, dbt, Spark, data infrastructure \|
10	\| data-analyst \| Dashboards, BI reports, SQL queries, KPIs, metrics, data exploration \|
11	\| data-scientist \| ML models, statistical analysis, predictive analytics, experiments \|
12	\| qa-engineer \| Test automation, CI/CD testing, data quality validation, regression testing \|
13
14	## Examples
15
16	- "Build an ETL pipeline to sync Stripe data to our warehouse" -> data-engineer
17	- "Create a dashboard showing monthly revenue by product" -> data-analyst
18	- "Train a churn prediction model on our user data" -> data-scientist
19	- "Set up automated data quality checks for the pipeline" -> qa-engineer
20	- "Migrate our data warehouse from Redshift to BigQuery" -> data-engineer
21	- "Analyze conversion funnel drop-off rates" -> data-analyst
22
23	## Workflow
24
25	1. Identify whether the request is about data infrastructure, analysis, modeling, or testing.
26	2. For requests spanning multiple areas (e.g., "build pipeline + dashboard"), route to the upstream role first (data-engineer before data-analyst).
27	3. For ambiguous data requests, default to data-analyst.
28	4. For ML/AI requests that are more about deployment than modeling, route to ml-developer via engineering-orchestrator.

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Type