joi
Joi
Quick Start
const Joi = require('joi');
const schema = Joi.object({
name: Joi.string().min(1).max(100).required(),
age: Joi.number().integer().min(0),
email: Joi.string().email()
});
const { error, value } = schema.validate(input);
Critical Rules
- Schemas are immutable - Every method returns a new schema instance; never mutate
More from damusix/skills
htmx
Implements HTMX interactions, configures swap behaviors, debugs hx-* requests, and builds hypermedia-driven UI components. Use when tasks involve hx-* attributes, HTMX AJAX requests, swap strategies, server-sent events, WebSockets, or hypermedia-driven UIs.
90hapi
Creates, configures, and debugs `@hapi/hapi` servers — implements routes, plugins, auth schemes, validation, caching, and request lifecycle hooks. Use when building HTTP APIs, setting up stale-while-revalidate caching, registering server methods, configuring views, managing startup sequences, or troubleshooting response marshalling.
32mssql-server
Writes, optimizes, and debugs T-SQL queries. Explains SQL Server internals, troubleshoots performance issues, and guides database administration tasks including backup/restore, high availability, security, and index design. Use when the user asks about T-SQL syntax, SQL Server administration, query performance, stored procedures, indexes, locking, transactions, backup/restore, high availability, security, or any MSSQL-related topic — even without saying 'SQL Server' explicitly. Also trigger on terms like SSMS, tempdb, bcp, sqlcmd, MSSQL, sp_executesql, NOLOCK, columnstore, Hekaton, RCSI, param sniffing, or execution plan.
31google-zx-scripting
Writes and executes JavaScript-based shell scripts using Google's zx library. Use when writing shell scripts, automation, build tools, file processing, CLI tools, deployment scripts, data pipelines, or batch operations. Also covers piping, streams, parallel execution, retries, cross-platform scripting, built-in fs utilities, and minimist argument parsing.
26sql-ml-features
Use when preparing data for machine learning from SQL Server — feature engineering in T-SQL, building training/test datasets, statistical aggregations for ML pipelines, sampling strategies, data normalization and encoding in SQL, writing queries that feed pandas or scikit-learn, exporting to Parquet or CSV for model training, or when a data scientist asks for a 'feature table' or 'training set' from a SQL Server database.
10sql-bi-reporting
Use when writing T-SQL for business intelligence, analytics, or reporting. Includes building summary reports with GROUPING SETS, ROLLUP, and CUBE, writing time-series queries with date bucketing, creating pivot/unpivot transformations, generating tally/numbers tables for gap-filling, building running totals and moving averages with window functions, writing year-over-year comparisons, designing materialized views for dashboards, or producing CSV/JSON exports from SQL Server.
9