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Found 151 Skills
Data engineering skill for building scalable data pipelines, ETL/ELT systems, and data infrastructure. Expertise in Python, SQL, Spark, Airflow, dbt, Kafka, and modern data stack. Includes data modeling, pipeline orchestration, data quality, and DataOps. Use when designing data architectures, building data pipelines, optimizing data workflows, implementing data governance, or troubleshooting data issues.
Push Packer build metadata to HCP Packer registry for tracking and managing image lifecycle. Use when integrating Packer builds with HCP Packer for version control and governance.
Implement data quality checks, validation rules, and monitoring. Use when ensuring data quality, validating data pipelines, or implementing data governance.
Screen and analyze stocks through an ESG (Environmental, Social, Governance) lens, evaluating sustainability practices, controversy exposure, and responsible investing criteria. Use when the user asks about ESG investing, sustainable investing, socially responsible investing (SRI), impact investing, green stocks, carbon footprint analysis, governance quality assessment, controversy screening, exclusion lists, or ESG scoring of companies or portfolios.
Analyze proxy statements (DEF 14A) to extract executive compensation, governance information, and shareholder voting matters using Octagon MCP. Use when researching CEO pay, board composition, say-on-pay votes, and corporate governance practices.
Audit GitHub repository branch governance and workflow hygiene. Use when asked to review rulesets, required status checks, update restrictions, delete-on-merge settings, auto-merge workflow reliability, stale branches, ghost workflow registrations, or branch-policy drift.
Apply and enforce cloud resource tagging strategies across AWS, Azure, GCP, and Kubernetes for cost allocation, ownership tracking, compliance, and automation. Use when implementing cloud governance, optimizing costs, or automating infrastructure management.
Design and implement Azure cloud architectures using best practices for compute, storage, databases, AI services, networking, and governance. Use when building applications on Microsoft Azure or migrating workloads to Azure cloud platform.
Use when structuring pillar calendars, approvals, and cadence governance.
Executable documentation governance with compound engineering and abductive learning. Enforces the Seven Laws through type compilation, schema validation, and hookify-based enforcement. Implements programmatic compound engineering where K' = K ∪ crystallize(assess(τ)) for monotonic knowledge growth. Integrates abstracted abductive learning (OHPT protocol) for systematic debugging and pattern extraction. Trigger when writing code, debugging, establishing governance, or when mentioned vibecode, compound, abductive, or executable documentation. Self-validating and homoiconic.
Use when defining events, fields, and governance for GTM analytics pipelines.
AI governance audit using ISO 42001 standard. Ensures AI systems are developed and deployed responsibly with risk management, ethics, security, transparency, and compliance best practices.