Generates code from mathematical expressions
A secure and scalable Git MCP server enabling AI agents to perform comprehensive Git version control operations via STDIO and Streamable HTTP.
CLI entry point for AgentV
Agent-native TypeScript framework for building MCP servers. Declarative definitions with auth, multi-backend storage, OpenTelemetry, and first-class support for Bun/Node/Cloudflare Workers.
Server-Sent Events transport for Hono and Model Context Protocol
TypeScript SDK and CLI for evaluating agentskills.io-style AI agent skills with LLM judges, baseline comparison, YAML config, JSONL logs, and HTML reports.
Source-grounded, eval-gated knowledge growth primitives for agents.
MongoDB Shell CLI REPL Package
Run code inside a hidden Electron window
Shape Expressions triple expression evaluator api - defines how @shexjs/validator invokes regex evaluators.
CLI for Vally — the evaluation platform for AI agents
Utility for parsing and converting ROS Xacro files in Javascript.
MongoDB Shell CLI REPL
Statsig helps you move faster with feature gates (feature flags), and/or dynamic configs. It also allows you to run A/B/n tests to validate your new features and understand their impact on your KPIs. If you're new to Statsig, check out our product and cre
Javascript sandboxing library.
CodeMirror plugin for Model Context Provider
A safe callback to string serializer
Runs domain agents and automates improving them from their own traces — chat turns and loop topologies, with an analyst→prompt/knowledge→eval-gated-ship self-improvement loop.
Stringify is to `eval` as `JSON.stringify` is to `JSON.parse`
A fork of the jexl lang for jbrowse
Statsig helps you move faster with feature gates (feature flags), and/or dynamic configs. It also allows you to run A/B/n tests to validate your new features and understand their impact on your KPIs. If you're new to Statsig, check out our product and cre
Smaller than base64, only use ASCII, can run in web browser.
API called by @shexjs/validator to get a neighborhood (arcs in and out of a node)
Agent evaluation framework with LLM-based grading for AI agent quality assessment