AI · alternatives · 2026
24 alternatives to skillaudit.sh
h3ll0 HN, I’ve spent the last 15 years in offensive security, and if there's one thing I've learned, it's that every new technology—no matter how advanced—brings its own unique breed of exploitable flaws. LLMs and autonomous agents are no exception. While they feel like "magic," from a security perspective, they are just another attack surface with specific vulnerabilities in how they define and execute "skills." we built skillaudit.sh because I wanted a minimalist, lightweight tool to audit these new skill definitions without the overhead of heavy frameworks. It focuses on the practical,…
Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.
- 1SkillShield▲73
Security-scored directory for AI skills and agent tools
Feb 2026 · skillshield.io · its alternatives →
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Skillkit▲252It's an open-source project that lets you create, translate, and work with multiple agents at the same time, and more.
Feb 2026 · agenstskills.com · its alternatives →
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Trails▲81Hey all, Justin here. I previously built Phind, the AI search engine for developers. One of the biggest problems we had there was figuring out what went wrong with bad searches. We had tons of searches per day, but less than 1% of users gave any explicit feedback. So we were either manually digging through searches or making general system improvements and hoping they helped. This problem gets harder with agents. Traces are longer and more complex. It takes more effort to review them, so I'm building a tool that lets you analyze LLM outputs directly to help developers of LLM apps and agents…
Jan 2026 · trails-red.vercel.app · its alternatives →
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Agent Skills▲190Curated agent-skills: 1,000+ practical skills selected from 63,000+ GitHub skills. Filter by newest/hot/installs. Works with Claude Code, Codex, ChatGPT, and Cursor.
Mar 2026 · agentskill.sh · its alternatives →
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Audit your AI agent skills to avoid malware
Apr 2026 · labs.snyk.io · its alternatives →
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skillgaurd▲11Detect Security Threats in Agent Skills
Jan 2026 · skillgaurd.up.railway.app · its alternatives →
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Skilled▲76Dashboard to find agent skills you no longer need
May 2026 · github.com · its alternatives →
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vett▲5Hey HN. I built a security registry for AI agent skills. There are 64k skills on Vercel's skills.sh. Cursor, Claude Code, Windsurf, and dozens more agents pull them from GitHub at HEAD — no versioning, signing, or scanning. The OpenClaw agents themselves flagged this: "The supply chain attack nobody is talking about: skill.md is an unsigned binary."[0] I took an official skill that packages other skills, added a few lines of Python to exfiltrate env vars, shell history, and git config, and installed it into Claude Code and Codex. Claude Code ran the script without flagging the outbound…
Feb 2026 · vett.sh · its alternatives →
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Hi HN, Matvey, Ildar, Joey, and Dominik here. If you're building LLM agents that use tools, you're probably worried about prompt injection attacks that can hijack those tools. We were too, and found that solutions like prompt-based filtering or secondary "guard" LLMs can be unreliable. Our thesis is that agent security should be handled at the network level between the agent and the LLM, just like a traditional web application firewall. So we built Archestra Platform: an open-source gateway that acts as a secure proxy for your AI agents. It's designed to be a deterministic firewall against…
2025 · archestra.ai · its alternatives →
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I created this tool after writing a few agent skills by hand and noticing this pattern was repetitive. Paste a documentation URL, enter your own model API key, and it gets the page content client-side to create a reusable SKILL.md. There is no backend/proxy, so it stays as secure as possible. I would like feedback on the structure of the output and the edge cases.
May 2026 · getskillify.dev · its alternatives →
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Hi HN — I'm Scott. Skillscript is a small language I built to write what I want my local agent to actually do, in a form I can read and version, instead of hoping the model gets it right each time. The itch started with something small. I wanted my NanoClaw agent to run my morning brief the same way every day. Check overnight tickets, summarize the deploy pipeline, flag anything urgent. Every session, it would re-figure out how to do this from scratch, drift a little, and cost tokens for what's basically a fixed procedure. I could put it in a system prompt or an MD skill file, but those are…
Jul 2026 · github.com · its alternatives →
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I built a collection of webhook skills because AI coding agents are surprisingly bad at webhook integrations. The generated code looks reasonable until you run it, then signature verification fails, raw body handling is wrong, or the middleware order breaks everything. PostHog's research on LLM code generation (https://posthog.com/blog/correct-llm-code-generation) found that agents produce more reliable code when referencing known-working examples rather than reconstructing from training data. That's the approach here. `webhook-skills` is a collection of provider-specific…
Feb 2026 · github.com · its alternatives →
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Give your AI agent expert skills before it builds
May 2026 · npmjs.com · its alternatives →
- 16
New ways of breaking app-integrated LLMs . Contribute to greshake/llm-security development by creating an account on GitHub.
2023 · github.com · its alternatives →
- 17IS
Hey HN! For that last 8 months I've been trying to make agents that can hack web applications to find vulnerabilities in them - An AI Security Tester. The system has 29 agents in total, a custom LLM Orchestration framework which works on the task-subtask architecture (old-school but works amazingly for my use case, and is pretty reliable) with custom agent calling mechanism. No Auo-Gen, Langchain and Crew AI - Everything custom built for pentesting. Each test runs in an isolated Kali linux environment (on AWS Fargate), where the agents have full access to the environment to undertake any…
2025 · its alternatives →
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Every time I wanted to use LLMs in my existing pipelines the integration was very bloated, complex, and too slow. This is why I created a lightweight library that works just like scikit-learn, the flow generally follows a pipeline-like structure where you “fit” (learn) a skill from sample data or an instruction set, then “predict” (apply the skill) to new data, returning structured results. High-Level Concept Flow Your Data --> Load Skill / Learn Skill --> Create Tasks --> Run Tasks --> Structured Results --> Downstream Steps And the bast part: Every step can be saved and reused as…
2025 · github.com · its alternatives →
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Hi Hacker News! I’m Ritam, working with the small but mighty team at Nori. We’ve been obsessed in recent months with how to take tools like Claude Code from “I’ll experiment around with this” to “This is the most useful and necessary thing I use every day”. When I first sat down with our team to check out what they’d built, I found my skepticism about agentic coding melting away—they’d built useful, high quality, handwritten skills, instructions that functioned as “skillsets” to tie skills together for consistent and replicable results, and tooling to manage loading the right context for the…
Jan 2026 · noriskillsets.dev · its alternatives →
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Hi HN, I’m the creator of Cordum. I’ve been working in DevOps and infrastructure for years (currently in the fintech/security space), and as I started playing with AI agents, I noticed a scary pattern. Most "safety" mechanisms rely on system prompts ("Please don't do X") or flimsy Python logic inside the agent itself. If we treat agents as autonomous employees, giving them root access and hoping they listen to instructions felt insane to me. I wanted a way to enforce hard constraints that the LLM cannot override, no matter how "jailbroken" it gets. So I built Cordum. It’s an open-source…
Jan 2026 · github.com · its alternatives →
- 21OS
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…
Jan 2026 · its alternatives →
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The original AI skills security directory
Feb 2026 · skillshield.dev · its alternatives →
- 24
Discover 172K+ AI agent skills for Claude, Codex & Copilot
Feb 2026 · skills.palebluedot.live · its alternatives →
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