Search Results for "javascript form validation"
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Showing 8 open source projects for "javascript form validation"
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Archify
Agent skill for beautiful, verifiable architecture, workflow
Archify is an agent skill and rendering system for turning codebases or system descriptions into polished technical diagrams. It works with coding agents such as Claude Code, Codex CLI, Cursor, and OpenCode. Agents generate typed JSON representations that Archify deterministically compiles into self-contained HTML and SVG. It supports architecture, workflow, sequence, data-flow, and lifecycle diagrams. Interactive viewers provide search, route tracing, upstream and downstream exploration,... -
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ego (lite)
The fastest browser for AI agents to run web automation
...Optional Chrome data migration carries over logins, cookies, extensions, and bookmarks so agents can use authenticated sessions with less setup. The ego-browser skill connects tools such as Codex, Claude Code, Cursor, and custom agent CLIs to the browser. Agents interact through JavaScript tools for navigation, snapshots, form entry, clicks, waiting, and captures. Browser data remains on the device, and users can observe, stop, or take control of an agent's Space. Windows and Linux versions are listed as future work rather than currently supported releases. -
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Superpowers
An agentic skills framework & software development methodology
Superpowers Framework is a widely-used agentic skills framework and methodology for software development that equips coding agents like Claude Code with structured capabilities to plan, develop, test, and review code systematically. Instead of simply generating code, Superpowers drives an AI through a thoughtful software engineering workflow that starts with clarifying project intent, teasing out a detailed specification, and creating an implementation plan that is readable and actionable.... -
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unlazy
Anti-laziness skill for AI agents. Core: the Depth Tree method
unlazy is an AI-agent skill designed to enforce disciplined completion and verification on substantial tasks. It requires agents to define acceptance gates before claiming that work is finished. Each gate can specify a command, expected result, working directory, and recorded evidence. A bundled checker validates the ledger, runs approved checks, and can reverify previously completed work. The workflow emphasizes reviewing returned work and reporting only conclusions supported by verifiable... -
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Browserbase Skills
Claude Agent SDK with a web browsing tool
Browserbase Skills is a collection of reusable automation “skills” designed to enable AI agents to interact with web environments programmatically. It provides structured workflows that abstract browser actions such as navigation, form filling, and data extraction into composable building blocks. The system is intended to simplify the development of browser-based agents by offering prebuilt capabilities that can be orchestrated together. It integrates with headless browser infrastructure,... -
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Evolver
The GEP-Powered Self-Evolution Engine for AI Agents
Evolver is the core engine behind EvoMap and is positioned as a self-evolution system for AI agents rather than a conventional application framework. Its purpose is to turn isolated prompt adjustments into reusable, auditable evolution assets, giving agent teams a more structured way to improve behavior over time. The project uses a protocol-constrained approach centered on concepts such as genes, capsules, and events, which are stored as structured assets and selected through signal... -
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DevOpsGPT
Multi agent system for AI-driven software development
Welcome to the AI Driven Software Development Automation Solution, abbreviated as DevOpsGPT. We combine LLM (Large Language Model) with DevOps tools to convert natural language requirements into working software. This innovative feature greatly improves development efficiency, shortens development cycles, and reduces communication costs, resulting in higher-quality software delivery. The automated software development process significantly reduces delivery time, accelerating software... -
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ADSKIT
Agents design supporting system for simulation models
Main task is automating the creation of simulation models of complex model. The originalities of proposed software are explicit representation of conceptual model in the concept – attribute – relation form and applying expert system approach to transform designed ontology into agent model. Researchers develop the structure and behavior of agents using declarative approach. Web: https://84.237.20.67/RFFI/Main.php
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