Schema Validator - Auto-activating skill for Data Pipelines. Triggers on: schema validator, schema validator Part of the Data Pipelines skill category.
33
Quality
3%
Does it follow best practices?
Impact
83%
1.07xAverage score across 3 eval scenarios
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./planned-skills/generated/11-data-pipelines/schema-validator/SKILL.mdETL schema validation
Standard validation library
0%
0%
Common schema standard
20%
0%
Type validation
75%
62%
Required field validation
100%
100%
Range or constraint validation
100%
100%
Production-ready completeness
100%
100%
Error collection
100%
100%
Step-by-step flow
100%
100%
Schema definition separation
40%
30%
ETL integration
62%
50%
Error details
100%
100%
Without context: $0.4324 · 1m 39s · 22 turns · 23 in / 6,345 out tokens
With context: $0.4647 · 1m 33s · 28 turns · 136 in / 5,817 out tokens
Airflow workflow schema gate
Airflow DAG structure
100%
100%
Validation as DAG task
100%
100%
Upstream dependency ordering
100%
100%
Fail-on-invalid behavior
100%
100%
Recognized schema standard
0%
100%
Schema definition separation
50%
100%
Error reporting
100%
100%
Production-ready completeness
100%
100%
Step-by-step validation flow
100%
100%
Airflow best practices
100%
100%
Without context: $0.2518 · 1m 4s · 13 turns · 14 in / 4,748 out tokens
With context: $0.5435 · 1m 50s · 27 turns · 281 in / 7,443 out tokens
Streaming event schema enforcement
Standard schema format
8%
16%
Schema definition separation
50%
70%
Step-by-step validation flow
90%
90%
Dead-letter queue routing
100%
100%
Error detail logging
100%
100%
Production-ready completeness
100%
100%
Streaming best practices
100%
100%
Industry-standard error handling
62%
87%
Type validation
75%
87%
Required field validation
100%
100%
Without context: $0.4273 · 1m 26s · 23 turns · 24 in / 5,612 out tokens
With context: $0.5207 · 1m 49s · 26 turns · 312 in / 7,000 out tokens
0c08951
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