validate-data Skill
Validate whether an analysis is accurate, well-supported, and ready to share or use for a decision. Use when reviewing methodology, calculations, comparisons, visuals, caveats, or conclusions. Published by openai in role-specific-plugins.
What is validate-data Skill?
Validate whether an analysis is accurate, well-supported, and ready to share or use for a decision. Use when reviewing methodology, calculations, comparisons, visuals, caveats, or conclusions. Published by openai in role-specific-plugins. This profile combines repository metadata with install, compatibility, and usage signals so developers can quickly decide whether it fits their agent workflow before opening the source repository.
Automated repository signals based on public metadata such as recency, license, installation evidence, and adoption. These are not a security audit or endorsement.
Key capabilities
- Includes SKILL.md support
- Reusable instructions support
- Database workflows
- Data analysis
- Database workflows use cases
- Data analysis use cases
Technical details
- Install or run with Copy skill directory
When to use validate-data Skill
- Use it for database workflows.
- Use it for data analysis.
Built with
Editorial notes
Source
- Creator: openai
- Repository: openai/role-specific-plugins
- Skill file: plugins/data-analytics/skills/validate-data/SKILL.md
What it does
Validate whether an analysis is accurate, well-supported, and ready to share or use for a decision. Use when reviewing methodology, calculations, comparisons, visuals, caveats, or conclusions.
Skill instructions
Related Skills Use $analyze-data-quality when validation depends on whether the underlying data is trustworthy, comparable, fresh, or at the right grain. Use $product-business-analysis when the task asks for a recommendation or decision after the validation pass. Validate Data Analysis Validate an analysis before it is shared with stakeholders. Focus on whether the question, data, methodology, calculations, visuals, claims, caveats, and recommendations are trustworthy enough for the stated audience and decision. This skill is for analysis QA, not raw dataset profiling alone. When validation depends on dataset reliability checks such as freshness, grain, missingness, duplicates, join coverage, or source mismatches, use $analyze-data-quality as a companion. Workflow 1. Inventory the artifact and claims. Identify the report, notebook, spreadsheet, SQL, dashboard, chart, pasted analysis, or recommendation being validated. Inspect source artifacts when a path, link, query, notebook, spreads
Explore related resources
Frequently asked questions
What is validate-data?
validate-data is a open-source AI agent skill with Copy skill directory. Validate whether an analysis is accurate, well-supported, and ready to share or use for a decision. Use when reviewing methodology, calculations, comparisons, visuals, caveats, or conclusions.
Who is validate-data best for?
validate-data is best for reusing agent instructions, scripts, and references, database workflows, data analysis workflows.
How do I install validate-data?
Install or run validate-data using Copy skill directory. Check validate-data for the latest setup command.
Is validate-data actively maintained?
validate-data may need a closer maintenance check before production use.
Auto-fetched from GitHub.
