Menú
Universal Numeric Fingerprint (UNF) generator. For strings, it splits into words and sorts them alphabetically to provide order-invariant fingerprints. Supports dataframes and files too.
Instalar con Codex o Claude Copia este prompt, pégalo en Codex, Claude u otro asistente, y deja que revise la página de la skill y la instale por ti.
Basado en la clasificación ocupacional SOC
Fetch and store transcripts from YouTube videos for deep content analysis.
Specialized in the MLCommons Croissant metadata specification. Can generate, validate, and serialize dataset metadata into compliant JSON-LD.
Send results and data files to stakeholders via email.
The Visual Systems Architect is an expert in translating complex technical requirements and infrastructure setups into structured, visually intuitive architectural diagrams (Mermaid.js).
Secure GitHub Orchestrator for Croissant Toolkit. Connect any repository, discovery skills, and audit ODRL sovereignty status.
ODRL Secure Login Interface. Uses authorization keys from ~/.odrl/authorize.did to automatically unpackage protected skills from the vault.
| name | unf |
| description | Universal Numeric Fingerprint (UNF) generator. For strings, it splits into words and sorts them alphabetically to provide order-invariant fingerprints. Supports dataframes and files too. |
The UNF (Universal Numeric Fingerprint) skill provides a robust mechanism for generating consistent data identifiers. Unlike traditional file hashes (like MD5 or SHA-256), a UNF is format-agnostic—meaning the same data values will produce the same hash regardless of whether they are stored in CSV, Parquet, SAS, or Stata.
unf_hash.py: CLI tool to compute a UNF for a string or file.dartfx-unf: High-performance Python implementation using the Polars engine.python3 .gemini/skills/unf/scripts/unf_hash.py "Data for fingerprinting"
python3 .gemini/skills/unf/scripts/unf_hash.py data/dataset.csv
python3 .gemini/skills/unf/scripts/unf_hash.py --json data/dataset.parquet