Run AI checks on paper subsections and record results in a validation ledger.
npx skills add https://github.com/hsigstad/research-kit --skill validate-section
Please help me install this Agent Skill. Skill: validate-section Source: https://github.com/hsigstad/research-kit/tree/main/skills/validate-section Command: npx skills add https://github.com/hsigstad/research-kit --skill validate-section
This Skill automates the validation of subsections in a paper by identifying its backing scripts, running AI checks, and recording results in a validation ledger.
To validate a subsection, use the validate-section skill with the section identifier: validate-section section-slug or validate-section section-number or validate-section heading-phrase.
High-intent search queries and answers about installing and using this skill.
To validate paper subsections, you run AI checks on the identified backing scripts and record the results in a validation ledger. This process checks narrative integrity, citation claims, and institutional facts to ensure document accuracy and consistency.
AI checks performed during paper validation include narrative integrity, citation claims, and institutional facts analysis. These checks analyze the text and interpret the results to ensure the subsection's accuracy and consistency.
Yes, you need Python and specific AI models to run AI checks on academic workflows. These dependencies are required for the text analysis and interpretation processes used to validate document subsections.
To start validating a specific section, use the validate-section skill with a section identifier. You can target the section using its slug, section number, or a heading phrase to initiate the AI validation process.
Recording document verification results in a validation ledger provides project memory and future reference. It logs the AI checks performed on subsections, ensuring that validation outcomes are tracked for ongoing quality assurance.
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