Cross-reference theory, resolutions, and source dossier to detect and resolve lesson inconsistencies.
npx skills add https://github.com/Nunopdmp/mvp_ai --skill m9-lesson-closer
Please help me install this Agent Skill. Skill: m9-lesson-closer Source: https://github.com/Nunopdmp/mvp_ai/tree/main/skills/m9-lesson-closer Command: npx skills add https://github.com/Nunopdmp/mvp_ai --skill m9-lesson-closer
This module provides a rigorous quality assurance pass for a complete lesson (theory + solved questions), ensuring coherence, comprehensiveness, and absence of contradictions across modules M8, M7, and the M4 source dossier, and surfaces actionable corrections to produce a finalized lesson document.
Review the complete lesson by validating theory, questions, and sources, identify gaps, apply safe auto-corrections, and generate a revised lesson text plus a diagnostic report.
High-intent search queries and answers about installing and using this skill.
To check lesson coherence, cross-reference the theory, the resolutions, and the source dossier to detect inconsistencies, validate answer keys, and generate a structured diagnostic report with a corrected lesson text.
Diagnosing pedagogical gaps requires an automated coherence check to detect pre-question and total lacunae, validate logical sequencing, and provide remediation guidance for missing content.
Validate jurisprudence and article references by enforcing rigorous checks against the source dossier, ensuring the lesson theory and resolved questions comprehensively match the original materials.
Yes, you can automatically fix answer key contradictions by testing gabaritos against the resolutions, applying safe auto-corrections, and flagging remaining issues for human review during the lesson revision.
Lesson quality assurance supports progression validation by checking prerequisites, verifying logical sequencing, and ensuring the pedagogical difficulty progression aligns across the theory and solved questions.
When auto-correcting lesson inconsistencies, the limitation is that not all issues can be resolved automatically; the system flags unresolved gaps and complex contradictions for mandatory human review.
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