Developer Tool / AI codebase readiness
Agentize is a Claude Code-oriented framework for assessing and improving how ready a codebase is for AI agents. It includes two maturity models, runnable assessment and improvement commands, and installable skills for project or personal use.
The page clearly describes a concrete AI developer tool with a focused purpose: evaluating and improving AI agent readiness and adoption in software projects. The snapshot shows the main models, the scoring criteria, install steps, and command-based workflows, which is enough for a useful public listing.
The snapshot does not show the full contents of READINESS.md, ADOPTION.md, or the Claude Code skills, so a visitor cannot tell how detailed the scoring rules or generated recommendations are. It also does not show screenshots, live demos, issue activity, or release history beyond the repository metadata.
Last evaluated 41 days ago. Current rank #473. Down 2 spots in the rankings.
WebLLM is a high-performance in-browser LLM inference engine that runs locally in the browser with WebGPU acceleration. It exposes an OpenAI-compatible API, supports streaming and JSON mode, and includes examples for building chat apps and browser extensions.
Self-hosted observability and control plane for production and coding AI agents, with live timelines, fleet-wide feeds, token budgets, MCP allow/block rules, and support for Claude Code plus a Python sensor.
Browser extension that scans pastes for credentials and PII before they reach LLM chat sites, with local on-device inference and no network calls.
Open-source runtime for multi-agent AI systems with job scheduling, DAG orchestration, shared memory, tool execution, and real-time observability.
