datHere, Inc.
Official@dathere · United States of America
Data Infrastructure Engineering with standards-based, best-of-breed, open source solutions to make your Data Useful, Usable & Used.
Agent Skills by datHere, Inc.
Showing 20 vetted skills indexed across 1 GitHub repositories.
datherevisual-data-dictionary
Generate an interactive HTML data dashboard driven by an LLM-inferred JSON Schema data dictionary from CSV files.
dathererelease-prep
Bump version numbers across qsv files and update the changelog for release preparation.
datherebuild-dashboard
Build self-contained HTML dashboards with embedded JSON data and Chart.js.
datherereview-respond
Batch-process pending GitHub PR review comments and apply fixes.
datheremcp-release-prep
Update MCP release version numbers across core files and generate a changelog entry.
datherebls-query
Map natural language topics to BLS series IDs and fetch values.
datheredata-join
Join two tabular datasets on a shared key using qsv joinp and sqlp.
datherecsv-wrangling
Automate CSV data wrangling workflows with qsv for indexing, profiling, transforming, and exporting.
datheredata-quality
Analyze and remediate data quality issues in tabular datasets.
datheregenai-disclaimer
Generate standardized GenAI disclaimers with short, medium, and full disclosure templates.
dathereinfer-ontology
Infer a semantic ontology from files and output ONTOLOGY.md.
datheredata-validate
Missing required data quality checks and/or duplicate/invalid entries in your own dataset.
datheredata-convert
Convert tabular data files between CSV, TSV, Excel, JSONL, and Parquet formats.
datheredata-viz
Profile and visualize tabular data from CSV, TSV, or Excel files.
datherecsv-query
Query CSV, TSV, and Excel files with SQL via the Polars-powered sqlp command.
dathereqsv-performance
Optimize qsv CSV workflows using index files, stats cache, and Polars commands.
datheredata-describe
Generate a data dictionary, description, and semantic tags for CSV, TSV, and Excel files.
datheredata-clean
Cleans CSV, TSV, and Excel files by normalizing headers and removing duplicates.
datherereproducible-analysis
Create and maintain a JSONL journal capturing data operations for reproducible analysis.
datheredata-profile
Profile tabular data files to extract structure, types, and distributions.
Frequently Asked Questions About datHere, Inc.
FAQPage SchemaWhat specific data tasks can be performed using these capabilities?▼
These capabilities enable high-speed tabular data wrangling, including format conversion between CSV, TSV, Excel, and Parquet. Users can perform complex SQL joins, execute data quality remediation, generate semantic ontologies, and build self-contained HTML dashboards with embedded JSON data for rapid reporting.
Which technical personas benefit most from these data engineering functions?▼
Data engineers, analysts, and researchers managing large-scale tabular datasets benefit most. These functions are designed for professionals requiring reproducible analysis, rigorous data quality validation, and efficient file-based query performance without the overhead of traditional relational database management systems.
What are the primary prerequisites for implementing these data processing functions?▼
Implementation requires a local environment capable of executing qsv-based commands. Users must have their tabular datasets prepared in standard formats like CSV, TSV, or Excel. The system relies on index files and stats caches to maintain high-performance query execution across large datasets.