OpenSkills - Run Claude Skills Locally Using Any LLM
OpenSkills: Run Claude Skills Locally using any LLM - instavm/open-skills
OpenSkills - Run Claude Skills Locally Using Any LLM launched on October 27, 2025 with 8 votes, #1,955 of 8,178 launches that month and more than 75% of that year's launches.
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localskills.shJul 2026 · localskills.sh · ▲115AI Skill & MCP server management for teams & enterprises
MakeSkill – The Intelligent Skill Builder for ClaudeNov 2025 · makeskill.cc · ▲9Creating high-quality skills for Claude manually is complex, requiring specific technical knowledge of the file system structure (like SKILL.md), YAML metadata configuration, and precise prompt engineering to ensure the agent behaves correctly. MakeSkill eliminates this friction by automating the technical implementation. Instead of writing code and configuration files from scratch, users interact with MakeSkill's AI to refine their ideas. The platform then generates the complete, optimized skill package—following all best practices—ready to be downloaded and imported directly into Claude…
- CICan I run this LLM? (locally)2025 · can-i-run-this-llm-blue.vercel.app · ▲42
One of the most frequent questions one faces while running LLMs locally is: I have xx RAM and yy GPU, Can I run zz LLM model ? I have vibe coded a simple application to help you with just that. Update: A lot of great feedback for me to improve the app. Thank you all.
- OSOpenSkills – Stop bloating your LLM context with unused instructionsJan 2026 · ▲9
Hello HN, I’ve been building AI agents lately and ran into a common "Context Bloat" problem. When an agent has 20+ skills, stuffing every system prompt, reference doc, and tool definition into a single request quickly hits token limits and degrades model performance (the "lost in the middle" problem). To solve this, I built OpenSkills, an open-source SDK that implements a Progressive Disclosure Architecture for agent skills. The Core Concept: Instead of loading everything upfront, OpenSkills splits a skill into three layers: Layer 1 (Metadata): Light-weight tags and triggers (always loaded…
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Source: Show HN post ↗
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I went down the rabbit hole on a side project and ended up building this: Strange Attractors(https://blog.shashanktomar.com/posts/strange-attractors). It’s built with three.js. Working on it reminded me of the little "maths for fun" exercises I used to do while learning programming in early days. Just trying things out, getting fascinated and geeky, and being surprised by the results. I spent way too much time on this, but it was extreme fun. My favorite part: someone pointed me to the Simone Attractor on Threads. It is a 2D attractor and I asked GPT to extrapolate it to…
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