parallelized discord discrimination seeker
Typescript-native, declarative DSL for working with binary data
Protocol layer for the pattern system. Base classes, event types, containers, tree utilities, the pitch type system, tuning infrastructure, and type discrimination. This is the extension point for building custom patterns and modifiers.
Assess compliance for AI in insurance underwriting, claims, and pricing. Covers algorithmic fairness, anti-discrimination, EU AI Act, state regulations, and actuarial standards.
Runtime utilities and shared types to drive type-safe API definitions. Powered by Typeweaver 🧵✨
Ark7 model used for both backend and frontend
ctxloom — The Universal Code Context Engine. A local-first MCP server providing intelligent code context via hybrid Vector + AST + Graph search with Skeletonization (92% token reduction).
Typescript-native, declarative DSL for working with binary data
The official TypeScript library for the Moderation API API
Local memory substrate for AI agents: persistent recall, hybrid retrieval, governed evolution, and memory safety.
A RETS client (Real Estate Transaction Standard).
Binary classifier system for multiple categories
Track federal preemption risks and state-federal regulatory friction. Monitor DOJ, Executive Orders, and federal courts for AI regulation challenges affecting Colorado SB 24-205, California SB 1047, and state compliance strategies.
ISI MCP Server — Persistent AI Identity Infrastructure powered by CCSP. Session lifecycle, contradiction detection, grounding verification, behavioral signature computation, and identity flywheel.
Link — the v1 entry point to the Mesh. Peer-to-peer agent ↔ agent over A2A v0.2 (JSON-RPC), mutual bearer auth, durable task store, no central service. See ADR-022.
data access object interface with support for pluggable implementations based on versioned specs
Dedicated js/ts client for Flotiq API which focuses on type safety and IDE autocompletion of user data types.
Sigil, bulletproof class identity for large TypeScript projects
A lightweight, file-based ODM Database for Node.js, inspired by Mongoose
A Javascript library for the Cascade CMS API
Six small text classifiers and a train() primitive that run in the browser or in Node and return calibrated probabilities.
AlgoVoi substrate-author layer for JCS+PQC integration: signature_algorithm open-enum + cross-implementor byte-anchor convergence proof. TypeScript companion to algovoi-substrate-pqc on PyPI.
NPM package to extract full transcripts from C-Span videos
A RETS client (Real Estate Transaction Standard).
Generic worst-case-linear-time sorting and partitioning algorithms based on discriminators
A small utility for partitioning a sequence of items by enum discriminant
Procedural macro to add functions on enum types to get discrimnant value from variant or create unit variant from discriminant value.
A tiny crate to make working with discriminants easier.
A tiny crate to make working with discriminants easier.
Atlas Program Library 8-Byte Discriminator Management
Solana Program Library 8-Byte Discriminator Management
Solana Program Library 8-Byte Discriminator Management
Solarti Program Library 8-Byte Discriminator Management
Solana Program Library 8-Byte Discriminator Management
Trezoa Program Library 8-Byte Discriminator Management
proc_macros intended for use with split_by_discriminant
A simple discriminant gem
A Ruby gem that implements single-table inheritance (STI) for ActiveRecord models using string, integer and boolean column types.
Discriminate class type based on a model field
harlequin is a Ruby wrapper for linear and quadratic discriminant analysis in R for statistical classification. Also allows means testing to determine significance of discriminant variables.
Add MCP tool serving to any Rails app. Write @rbs type annotations with predicate tags (@requires, @feature, or custom) and the gem compiles per-user JSON Schema automatically — filtering fields by permissions, feature flags, and plan tiers at request time.
Rumale::MetricLearning provides metric learning algorithms, such as Fisher Discriminant Analysis and Neighboourhood Component Analysis with Rumale interface.
Flexible Argument Parse It allows a default setting to use discriminating argument types like 'a:42 -b c,3,4 delta:1..10'
Rumale is a machine learning library in Ruby. Rumale provides machine learning algorithms with interfaces similar to Scikit-Learn in Python. Rumale supports Support Vector Machine, Logistic Regression, Ridge, Lasso, Multi-layer Perceptron, Naive Bayes, Decision Tree, Gradient Tree Boosting, Random Forest, K-Means, Gaussian Mixture Model, DBSCAN, Spectral Clustering, Mutidimensional Scaling, t-SNE, Fisher Discriminant Analysis, Neighbourhood Component Analysis, Principal Component Analysis, Non-negative Matrix Factorization, and many other algorithms.
Validrb is a powerful Ruby schema validation library inspired by Pydantic and Zod. It provides type coercion, rich constraints, schema composition, union types, discriminated unions, custom validators, JSON Schema generation, and serialization.
A lightweight Ruby gem providing generic Solana building blocks — JSON-RPC client with retry, Ed25519 keypair management, Borsh encoding/decoding, transaction builder with PDA derivation and Anchor discriminators, SPL Token instruction helpers, and a pure-Ruby wallet-signature verifier (Solana::AuthVerifier).
swagger23 converts Swagger 2.0 (OAS 2) API specifications into OpenAPI 3.0.3 (OAS 3) specifications. Accepts JSON or YAML input, produces JSON or YAML output. Works as a Ruby library (Swagger23.convert) or a standalone CLI tool (swagger23). Handles paths, parameters, requestBody, components/schemas, securitySchemes, servers, $ref rewriting, collectionFormat, x-nullable, discriminator, OAuth2 flows, and file uploads. No external runtime dependencies. Safe for large specs.
IrtRuby is a comprehensive Ruby library for Item Response Theory (IRT) analysis, commonly used in educational assessment, psychological testing, and survey research. Features three core IRT models: • Rasch Model (1PL) - Simple difficulty-only model • Two-Parameter Model (2PL) - Adds item discrimination • Three-Parameter Model (3PL) - Includes guessing parameter Key capabilities: • Robust gradient ascent optimization with adaptive learning rates • Flexible missing data strategies (ignore, treat as incorrect/correct) • Comprehensive performance benchmarking suite • Memory-efficient implementation with excellent scaling • Production-ready with extensive test coverage Perfect for researchers, data scientists, and developers working with educational assessments, psychological measurements, or any binary response data where item and person parameters need to be estimated simultaneously.
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