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review-recipes

Validate microbial media recipe records for LinkML schema and CultureMech ID compliance.

10|3|Updated Jan 28, 2026
Search Tags:#knowledge graph#validation#batch reporting#schema checking#recipe QA#ontology linkage#data quality fixes
One-click install
npx skills add https://github.com/CultureBotAI/CultureMech --skill review-recipes
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: review-recipes
Source: https://github.com/CultureBotAI/CultureMech/tree/main/.claude/skills/review-recipes
Command: npx skills add https://github.com/CultureBotAI/CultureMech --skill review-recipes

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

The Review Recipes skill prevents invalid or low-quality microbial media recipe records from entering CultureMech by catching schema violations, broken identifiers, incorrect ontology linkages, and inconsistent preparation metadata before KG export.

Core Features & Use Cases

  • Schema validation for recipes and solutions: Confirms required fields, enum values, and LinkML schema compliance so downstream KG export won’t fail.
  • Ingredient and ontology linkage checks: Verifies MediaIngredientMech IDs exist and that CHEBI/ontology term mappings are resolvable, highlighting unmapped ingredients and placeholders.
  • Cross-reference validation: Ensures solution references and ingredient composition relationships are internally consistent.
  • Data quality scoring with actionable priorities: Groups findings into P1–P4 with rules tailored to export-blocking errors versus enrichment opportunities.
  • Batch reporting and safe auto-fixes: Generates human- and machine-readable validation reports and applies limited “safe corrections” (e.g., units normalization, placeholder removal) when appropriate.

Quick Start

Run a batch pre-export validation for all recipes with P1–P3 filtering and generate an HTML dashboard report.

Frequently Asked Questions about review-recipes

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I validate microbial growth media recipes against a LinkML schema before export?▼

To validate microbial growth media recipes against a LinkML schema, run batch or single-recipe checks to confirm required fields, enum values, and schema compliance, preventing export-breaking errors and broken cross-references in your knowledge graph.

Why does knowledge graph export fail when ontology linkage is broken?▼

Knowledge graph export fails when ontology linkage is broken because unresolved CHEBI term mappings and invalid MediaIngredientMech identifiers create inconsistent cross-references, blocking downstream data integration and invalidating the solution reference consistency.

Can I automatically fix data quality issues during batch recipe validation?▼

Yes, during batch recipe validation you can apply limited safe auto-corrections such as units normalization and placeholder removal, generating both human-readable and machine-readable reports filtered by priority levels from P1 to P4.

What is the best way to check CHEBI ontology mappings for microbial media ingredients?▼

The best way to check CHEBI ontology mappings for microbial media ingredients is to run a validation pass that verifies MediaIngredientMech IDs exist and confirms term mappings are resolvable, highlighting unmapped ingredients and placeholders.

How do cross-reference validation checks ensure solution reference consistency in recipe records?▼

Cross-reference validation ensures solution reference consistency by verifying that ingredient composition relationships and solution references are internally consistent, preventing broken cross-references and ensuring CultureMech ID integrity before committing records.

What limitations exist when applying safe auto-fixes to data quality issues in recipe records?▼

Safe auto-fixes for data quality issues in recipe records are limited to specific safe corrections like units normalization and placeholder removal, meaning complex schema violations or broken ontology linkages require manual data quality fixes.

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