Skill Extractor is an open-source tool that mines reusable coding-agent skills from Claude Code, Codex CLI, or other agent transcripts. Instead of relying on opaque memory, it reads local traces, redacts secrets, scores candidate lessons by confidence and utility, weights them by whether the originating run succeeded, and puts each proposed skill into a review queue before anything becomes persistent instruction. Developers can approve, edit, or reject suggestions from a VS Code panel, a Claude Code slash command, or the raw CLI, with approved output written as normal SKILL.md files. It is useful for solo developers and teams that repeatedly teach agents the same project habits. The official Apache-2.0 GitHub repository verifies docs, hooks, examples, security notes, and a July 2026 release.
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codemap is an MIT-licensed project brain for AI coding tools that gives LLMs instant architectural context from your codebase without burning tokens. It generates a fast tree/context view, dependency flow, dependency blast-radius analysis, and a layered handoff format for cross-agent continuation, then exposes everything through a JSON context bundle and an MCP server compatible with Claude Code and Codex. A built-in Codex plugin and community skill registry make it easy to install and share. Developers use codemap to onboard agents to large repos in seconds, keep session continuity across handoffs, and scope the impact of a change before running it.
Type.com is a multiplayer AI workspace where teams collaborate with Claude, Codex and other models in a shared company context. It brings conversations, files, skills, integrations and automations into collaborative Spaces instead of leaving useful work trapped in individual chat windows. Marketing, sales, support and operations teams can tag Type from Slack or email, share access through role-based permissions, and build custom dashboards or internal apps grounded in company knowledge. Type also supports OAuth, MCP and API connections, with granular controls for users and spaces. It is notable now because its Product Hunt launch presents a practical answer to the coordination problem emerging as teams adopt multiple coding and general-purpose agents. The official site confirms a shipped cloud workspace with desktop and mobile access, not merely an agent concept.
Ollama is a local AI platform for running, managing, and sharing open models on your own machine or private infrastructure. It makes it easy to pull models, serve them through an API, and integrate local inference into developer workflows without relying on a fully managed cloud stack. Teams use Ollama for privacy-sensitive assistants, internal tools, offline experimentation, and rapid testing of open-weight models across laptops, workstations, and servers. It is especially useful for developers, operators, and AI builders who want quick setup with less operational overhead. What makes Ollama distinctive is how approachable it is: it packages model runtime, distribution, and deployment into a streamlined experience that helps people get productive with local AI in minutes instead of spending days on configuration.
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