tower.dev
Official@tower · United States of America
Tower Computing, Inc.
Agent Skills by tower.dev
Showing 13 vetted skills indexed across 1 GitHub repositories.
towerfind-destination
Identify and configure DLT destinations with authentication details and configuration steps.
towerplan-business-analyst-review
Validate data-app requests and generate BA review artifacts with scope decisions.
towerinit-tower-app
Detect project context and scaffold a Tower app or wrap a Python pipeline.
towerplan-security-review
Audit credential hygiene and data sensitivity in Tower data apps.
towersetup-secrets
Manage credentials as runtime environment variables via Tower MCP.
towerplan-data-architect-review
Evaluate data model designs and dbt/dlt architectures for schema quality and evolution safety.
towercreate-rest-api-pipeline
Scaffold a deterministic dlt REST API pipeline for Tower apps.
towerplan-ops-review
Assess Tower data app readiness and generate a pre-deploy gating recommendation.
towerplan-data-engineer-review
Identify reliability gaps and production-readiness issues in Tower data apps.
towergather-context
Detect project stack and conventions to generate a structured project profile.
towerdata-analyst-explore
Profile loaded datasets to quantify completeness, freshness, consistency, queryability, and discoverability.
towerfind-source
Identify optimal DLT data source connectors for a given API or provider.
towerdebug-pipeline
Debug and inspect Tower app runs using local logs and status.
Frequently Asked Questions About tower.dev
FAQPage SchemaWhat specific tasks does Tower Computing enable for data teams?▼
Tower Computing enables the systematic scaffolding of dlt-based ingestion pipelines, the execution of formal data architecture and security reviews, and the profiling of dataset health. It provides structured gating recommendations for production deployments and ensures credential hygiene through managed environment variable configuration.
Which personas benefit most from Tower Computing?▼
Data engineers, data architects, and business analysts are the primary users. Data engineers utilize the platform for pipeline scaffolding and debugging, while architects and analysts leverage the review modules to validate schema quality, data sensitivity, and business scope requirements before production deployment.
What are the prerequisites for running Tower Computing?▼
Users require an existing dlt-based data environment and a project context compatible with Tower's scaffolding conventions. The platform functions by detecting local project stacks and requires standard access to environment variables for credential management and pipeline configuration.