Summary
This is a pre-delivery checklist for data analysis work that helps you catch mistakes before stakeholders see them. It walks through the usual suspects: source verification, null handling, date freshness, bad joins that double-count records, and whether your filters are actually doing what you think. There's also a calculation checks section that the preview cuts off. It's the kind of thing senior analysts keep in their heads but junior analysts should probably pin to their monitor. Honestly, the real value is having someone else's paranoia codified into a list you can actually run through instead of just generally worrying that you messed something up.
Install to Claude Code
npx -y skills add anthropics/knowledge-work-plugins --skill data-validation --agent claude-codeInstalls into .claude/skills of the current project.
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Files
SKILL.md
Select a file.
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Plug Mailtrap into your AI workflow and let it handle the email.
Connect Mailtrap MCP →Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →Make coding agent sessions - Searchable, Shareable, Vendor-neutral & Scored.
Try For Free →Your agent targets a perfect 10 Code Health score. Deterministic. Every commit.
Try For Free →Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →belt cli automatically finds the best tools and skills for your agent. image, video, music, tts...
one prompt install →
