Skillmarkdown
Agentic AI Skills Platform
Skillmarkdown launched on May 20, 2026 with 6 votes, #1,742 of 20,538 launches that month and more than 75% of that year's launches.
What it does
Skillmarkdown is the registry for agent skills. Discover, install, publish, and version reusable skills with dependable docs and CLI workflows.
Skillmarkdown is the agentic AI skills platform. Discover, install, publish, and version reusable skills with dependable docs and CLI workflows.
Publish once, install everywhere, and keep capabilities flexible. Publish once. Install everywhere. Keep capabilities flexible. Supports major agent providers. Stop rebuilding agent capabilities across repos. Publish skills once, discover what already exists, and manage versioned capabilities from one platform. Stop rebuilding agent capabilities across repos. Publish skills once, discover what already exists, and manage versioned capabilities from one platform. a single skill publish makes your skill available across every environment. One publish makes skills available everywhere. search the platform by name, keyword, or capability to find what already exists. Find existing skills fast.…from skillmarkdown.com
Does a similar job
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SkillkitFeb 2026 · agenstskills.com · ▲252It's an open-source project that lets you create, translate, and work with multiple agents at the same time, and more.
AI Skills RegistryJan 2026 · skillregistry.io · ▲6Discover and install AI skills, like Docker Hub for agents.
Craigslist for agent skills, curated by a humanSep 2026 · skillbay.sh · ▲28high quality AI skills marketplace. every skill is reviewed by a person and shows the same prompt answered without and with the skill. curated by @skeptrune.


Skills Hub, a desktop app for managing AI agent skills10d ago · github.com · ▲10A cross-platform desktop app to manage Agent Skills in one place and sync them to multiple AI coding tools’ global skills directories — “Install once, sync everywhere”. - qufei1993/skills-hub
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Hey HN, Henry here from Cactus. We open-sourced Needle, a 26M parameter function-calling (tool use) model. It runs at 6000 tok/s prefill and 1200 tok/s decode on consumer devices. We were always frustrated by the little effort made towards building agentic models that run on budget phones, so we conducted investigations that led to an observation: agentic experiences are built upon tool calling, and massive models are overkill for it. Tool calling is fundamentally retrieval-and-assembly (match query to tool name, extract argument values, emit JSON), not reasoning. Cross-attention…
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