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Data Validate

Data Validate reviews analyses for methodological soundness, calculation accuracy, and common analytical pitfalls before stakeholder presentation. It systematically checks data quality, spot-verifies aggregations, evaluates visualizations, and assesses whether conclusions are actually supported by the underlying data, then delivers a confidence rating and prioritized improvement suggestions.

Data Validate catches errors and validates methodology in analyses before you share them with stakeholders.

AI-generated summary based on this skill's SKILL.md

511 177 unlicensed, metadata onlyupdated by evolution-foundation

Decision gist · record as of 2026-05-13

Data Validate catches errors and validates methodology in analyses before you share them with stakeholders. Data Validate reviews analyses for methodological soundness, calculation accuracy, and common analytical pitfalls before stakeholder presentation. It systematically checks data quality, spot-verifies aggregations, evaluates visualizations, and assesses whether conclusions are actually supported by the underlying data, then delivers a confidence rating and prioritized improvement suggestions.

manual: git clone https://github.com/evolution-foundation/evo-nexus → cp -r evo-nexus ~/.claude/skills/data-validate

Use it when

  • Yes.
  • Data Validate systematically evaluates whether your dataset meets quality standards by checking for missing values, inconsistent formats.
Same gist for agents: .md · .json

Install

evolution-foundation/evo-nexus/data-validate · repository language: Python

generated, unverified - the skill's exact subdirectory could not be determined; check the repository on GitHub

Open directory. Skills are indexed for reading, not audited. Review a skill's body before installing it.

Frequently asked questions

AI-generated answers based on this skill's SKILL.md and metadata

What does Data Validate do?

Data Validate reviews analyses for methodological soundness, calculation accuracy, and common analytical pitfalls before stakeholder presentation. It systematically checks data quality, spot-verifies aggregations, evaluates visualizations, and assesses whether conclusions are actually supported by the underlying data, then delivers a confidence rating and prioritized improvement suggestions.

Can Data Validate check data for errors?

Yes. Data Validate catches errors before processing by validating data quality, spot-verifying calculations, and identifying common analytical pitfalls. It reviews structured data against rules and schemas to ensure accuracy and flag issues that could compromise your analysis or conclusions.

How does Data Validate ensure data consistency and completeness?

Data Validate systematically evaluates whether your dataset meets quality standards by checking for missing values, inconsistent formats, and incomplete records. It assesses data completeness across all fields and identifies gaps that could affect your analysis reliability.

Can Data Validate validate structured data like JSON or CSV?

Data Validate checks structured data against rules and schemas to validate format, data types, and field requirements. It reviews both JSON and CSV data to ensure they conform to expected structures before you process or analyze them further.

Does Data Validate automate data validation workflows?

Yes. Data Validate automates data validation by systematically checking data quality, verifying calculations, and assessing analytical conclusions without manual intervention. It delivers confidence ratings and prioritized improvement suggestions to streamline your validation process.

What confidence rating does Data Validate provide?

Data Validate delivers a confidence rating based on its comprehensive review of data quality, calculation accuracy, visualization soundness, and whether conclusions are supported by underlying data. This rating helps you understand the reliability of your analysis before presenting to stakeholders.

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Tags
quality-assurancedata-integrityerror-detectionschema-validationautomated-checking