Data Quality Frameworks
Implement data quality validation with Great Expectations, dbt tests, and data contracts. Use when building data quality pipelines, implementing validation rules, or establishing d
Hand-picked AI agent skills for product managers. Turn ambiguity into specs. Prompts for PRDs, user stories, prioritization frameworks, and stakeholder updates. Every entry is community-rated and free to copy — grab one and get to work.
Implement data quality validation with Great Expectations, dbt tests, and data contracts. Use when building data quality pipelines, implementing validation rules, or establishing d
Product Orchestrator agent. Reads the active story file, asks clarifying product questions one at a time, confirms task type (FRONTEND/BACKEND), and produces a complete unambiguous
Pulls recent production logs filtered for errors, warnings, and anomalies. Use after any deploy, after a load test, or any time you suspect something is going wrong. Treats logs as
Generate and maintain OpenAPI 3.1 specifications from code, design-first specs, and validation patterns. Use when creating API documentation, generating SDKs, or ensuring API contr
Master Julia 1.10+ with modern features, performance optimization, multiple dispatch, and production-ready practices. Expert in the Julia ecosystem including package management, sc
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