ORM

Scientific plotting with Prismatica - Prism-inspired Matplotlib styling toolkit for publication-ready figures. Use this skill for creating professional, publication-grade plots with consistent styling.

Proteomics analysis toolkit for label-free quantitative proteomics. Invokes R scripts for normalization, visualization (volcano, heatmap, PCA, LOPIT), pathway analysis (KEGG, ConsensusPathDB), and protein list cross-referencing (MISEV2018, SASP, Matrisome). USE WHEN user says 'analyze proteomics', 'volcano plot', 'normalize protein data', 'pathway enrichment', 'check EV markers', 'SASP analysis', 'matrisome', OR mentions q-value, fold-change, or protein quantification.

Configure bar and column charts in drizzle-cube dashboards with stacking, orientation, and grouping options. Use when creating bar charts, column charts, stacked bars, horizontal bars, or grouped bar visualizations.

Write scientific manuscripts with proper structure (IMRAD), citations (APA/AMA/Vancouver), figures/tables, and reporting guidelines (CONSORT/STROBE/PRISMA). Use when drafting any manuscript section, improving writing clarity, or preparing for journal submission.

dbt (data build tool) patterns for data transformation and analytics engineering. Use when building data models, implementing data quality tests, or managing data transformation pipelines.

Assists in writing high-quality content by conducting research, adding citations, improving hooks, iterating on outlines, and providing real-time feedback on each section. Transforms your writing process from solo effort to collaborative partnership.

Apache Airflow, Spark, Kafka, Flink, dbt, and modern data transformation tools

Query and analyze SEC filings and financial statements using EdgarTools. Get company data, filings, XBRL financials, and perform multi-company analysis.

Identifies, categorizes, and articulates code issues with brutal honesty and quantifiable specificity. Use when reviewing code, providing feedback, performing code audits, or when user needs direct assessment of code quality.

Define and configure database models with proper naming, relationships, timestamps, data types, constraints, and validation. Use this skill when creating or editing model files in app/Models/, Eloquent model classes, model relationships (hasMany, belongsTo, etc.), database table structures, model attributes and casts, model factories, or seeders. Use when working on model validation logic, database constraints, foreign key relationships, indexes, scopes, accessors, mutators, or any ORM-related model configuration.

Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation

Comprehensive read-only code review analyzing code quality, security vulnerabilities, performance issues, best practices compliance, and VSCode diagnostics. Use when user asks to review code, check for errors, analyze code quality, mentions security review, or wants feedback on their code.

Use when validating project structure during Standards Audit phase. Detects package type from package.json metasaver.projectType, loads structure rules from domain skills (react-app-structure, prisma-database, contracts-package), scans created/modified files, and reports violations with fix suggestions. File types: .tsx, .ts, directory layouts.

Design and build scalable backend systems, master database technologies, design APIs, implement authentication, and optimize performance. Use for backend design, database selection, API development, and scaling strategies.

Master database design, normalization, and data modeling.

Type-safe SQL ORM for TypeScript with zero runtime overhead

Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation

Expert knowledge of Google Cloud Build CI/CD pipelines including cloudbuild.yaml syntax, build steps, builders, substitution variables, triggers, secrets, artifact handling, and deployment to Cloud Run. Use when working with Cloud Build configurations, troubleshooting build pipelines, or deploying to Google Cloud Platform.

Expert database architecture including schema design, partitioning, replication, and performance optimization

Use this skill when creating, updating, or querying AI-optimized tracking artifacts (progress files, context notes, bug fixes, observation logs) in YAML+Markdown hybrid format for 95% token reduction. Invoke for: creating phase progress tracking, updating task status and blockers, querying pending work across phases, generating session handoff reports, validating artifact completeness, or migrating existing markdown files to hybrid format. Provides three embedded agents (artifact-tracker, artifact-query, artifact-validator) plus Python migration tools for efficient multi-phase project tracking.