catalyst-cooperative/pudl
skills/pudl/SKILL.md
Access PUDL table data plus table/column/source metadata in Jupyter or Marimo notebooks for debugging and visualization. Use when users ask what a table contains, how to read it, or how columns are defined.
development
Updated May 6, 2026
$ install --global
skillsauthnpx skillsauth add catalyst-cooperative/skills pudlInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
Security Scan Results
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
3
Scanners Passed
9
Scanners in report
Clean
TrivyContainer and dependency vulnerability scanner
95%
Clean
SemgrepStatic code analysis for vulnerabilities
95%
Clean
mcp-scan (Snyk)Model Context Protocol security validation
95%
Skipped
Snyk (dep)Open source security scanning
50%
Skipped
Socket.devSupply chain security analysis
50%
Skipped
VirusTotalMulti-engine malware detection
50%
Skipped
CrowdStrikeAdvanced threat intelligence
50%
Skipped
OSV-ScannerOpen Source Vulnerability database check
50%
Skipped
OWASP Dep-Check
50%
Last scanned: May 7, 2026, 7:38 AM121.9s1 file scanned
SKILL.md
- name:
- pudl
- description:
- >
- argument-hint:
- [table_name] [local|s3] [data|metadata|both]
PUDL Data and Metadata Guide
Use this skill for data-user workflows: reading PUDL outputs, understanding table and field semantics, tracing source context, and interpreting methodology.
Trigger phrases
- "show me this PUDL table in a notebook"
- "how do I read table X from Parquet"
- "load this table from local PUDL output"
- "read this PUDL table from S3"
- "what columns are in this table"
- "what does this column mean"
- "show table metadata for X"
- "which data source does this table come from"
- "find field descriptions for this table"
- "I need notebook code to explore this PUDL data"
Audience and scope
- Primary audience: analysts and data users, not core maintainers.
- Focus: using outputs and metadata confidently without digging into internals.
- Secondary audience: developers who need the same data context while coding.
Source-of-truth policy
The reference files in this skill are the canonical AI-facing layer for:
- data access and output usage patterns,
- table/field/source metadata retrieval,
- source-doc and methodology interpretation.
pudl-dev should reuse these references instead of duplicating them.
Reference index
- Data Access and Outputs
- Metadata and Querying
- Data Sources, Dictionaries, and Methodology
Escalation boundary
If a task requires modifying ETL code, schema migrations, dbt tests, or CI workflow,
hand off to pudl-dev and keep these references as the shared data context.
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