AI · alternatives · 2026
24 alternatives to Ratel, give agents unlimited tools and skills without context bloat
Hi HN! We're Giacomo and Roberto, authors of Ratel (https://github.com/ratel-ai/ratel) We used to help SaaS companies build agents on top of their products. Whenever we wanted to expand the agents’ complexity/scope, by adding more and more tools and instructions, we always run in the same issue: context bloat, with frequent hallucinations and sky high token bills. So we started constantly engineering the agents, dynamically loading tools, splitting them into subagents, inventing our own way to support skills And that's exactly when we started building Ratel: a…
Ratel is an open-source library that enables AI agents to access a full catalog of tools and skills without loading them all into context at once. It dynamically selects only relevant tools for each interaction… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Prices are shown for the 1 we have checked on their own sites, 1 of them free or with a free tier.
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PromptQL▲411Curating context is a second job nobody wants. PromptQL is the team brain that organizes itself. Work with your team in multiplayer AI threads, and PromptQL turns the context you generate into suggested edits to your wiki - interconnected pages that span skills, knowledge, and the semantic layer. Yo
Jul 2026 · promptql.io · its alternatives →
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Tessl▲260I'm Guy, the founder behind Snyk — now building Tessl, a package manager for agent skills. We’ve recently witnessed that most teams still treat skills as static artifacts: markdown files, created or copied from repo to repo. This approach offers a strong initial boost, but quickly creates debt: - Skills are duplicated, and updates never roll out. - Poor quality skills go unseen, misguiding agents instead of helping. - Skill knowledge grows stale, and don’t keep up with the systems and practices they describe. Without a way to evaluate skills, teams have no clear way to understand how good a…
Feb 2026 · tessl.io · its alternatives →
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Context Gateway▲220We built an open-source proxy that sits between coding agents (Claude Code, OpenClaw, etc.) and the LLM, compressing tool outputs before they enter the context window. Demo: https://www.youtube.com/watch?v=-vFZ6MPrwjw#t=9s. Motivation: Agents are terrible at managing context. A single file read or grep can dump thousands of tokens into the window, most of it noise. This isn't just expensive — it actively degrades quality. Long-context benchmarks consistently show steep accuracy drops as context grows (OpenAI's GPT-5.4 eval goes from 97.2% at 32k to 36.6% at 1M…
Mar 2026 · github.com · its alternatives →
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We recently shipped the Tiptap AI Toolkit (https://tiptap.dev/docs/content-ai/capabilities/ai-toolkit/o...), which lets developers embed LLM-powered editing into rich text editors. Now we’re exploring the next step: making agents operate on documents without a browser involved. The idea is a server-side system where agents can read, write, and transform documents in real time — essentially treating your document layer as a programmable data store that agents can interact with directly. Internally we’ve been joking about the name “real-time agentic document…
2025 · tiptap.dev · 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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Hello HN, I don't post on here much, but wanted to get some eyes on a new project I'm just launching. I think we definitely need one more AI code agent.. I'm a long-term C++ dev, and over 30+ years I've created some successful audio dev tools (JUCE, the Tracktion DAW, the Cmajor DSP language). All of these came from me getting annoyed with something I had to use, and deciding to have a go at my own take on whatever it was. So Juggler is my attempt at an AI code agent, after spending too many hours loving what the models could do, but hating the CLI experience, and having some opinions of…
Jul 2026 · github.com · its alternatives →
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Hey HN, I wanted to share a new project we've been working on for the last couple of months called ART (https://github.com/OpenPipe/ART). ART is a new open-source framework for training agents using reinforcement learning (RL). RL allows you to train an agent to perform better at any task whose outcome can be measured and quantified. There are many excellent projects focused on training LLMs with RL, such as GRPOTrainer (https://huggingface.co/docs/trl/main/en/grpo_trainer) and verl…
2025 · github.com · its alternatives →
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I've been exploring the (not so=) amazing potential of AI in coding and have compiled a list of tools. From AI-powered IDEs to code generators, this resource is my contribution to the community. I'm still on the fence about including txt2sql projects, as their functionality seems too basic to me. And I'm personally maintaining this, so your feedback is wellcome.
2025 · aicode.danvoronov.com · its alternatives →
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APIEval-20▲121An open benchmark for AI agents that test APIs
May 2026 · resources.kusho.ai · its alternatives →
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After training calculator agent via RL, I really wanted to go bigger! So I built RL infrastructure for training long-horizon terminal/coding agents that scales from 2x A100s to 32x H100s (~$1M worth of compute!) Without any training, my 32B agent hit #19 on Terminal-Bench leaderboard, beating Stanford's Terminus-Qwen3-235B-A22! With training... well, too expensive, but I bet the results would be good! *What I did*: - Created a Claude Code-inspired agent (system msg + tools) - Built Docker-isolated GRPO training where each rollout gets its own container - Developed a multi-agent…
2025 · github.com · its alternatives →
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Context Overflow▲109Hey HN, After using a bunch of agents, my friend and I noticed a major issue: an agent could spend a bunch of time solving a tricky task, but when the session ended all that knowledge vanishes. Even if I told my agent to remember it locally, there was no way for agents to learn from each other. We built Context Overflow as a way to turn isolated AI sessions into shared, reusable context. With Context Overflow, agents can: - Search through past solutions when starting a task - Ask questions when they get stuck - Share findings when they solve a non-trivial problem We support a variety of ways…
Mar 2026 · ctxoverflow.dev · its alternatives →
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Superexpert.AI▲107Hi HN — I built Superexpert.AI, an open‑source platform that lets you spin up multi‑task AI agents in minutes without writing any code (and lets you extend everything later). What it does - Plug‑and‑play agents – Create agents from a web form. Each agent can contain multiple tasks, and each task can run a different AI model, use its own tools, and follow custom instructions. - First‑class extensibility – Register a TypeScript function with registerServerTool, registerClientTool, or registerContextTool to add new functionality. If you want to share it, publish it as an NPM package and…
2025 · superexpert.ai · its alternatives →
- 14OS
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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Hey HN, Kyle here, one of the co-founders of OpenPipe. Reinforcement learning is one of the best techniques for making agents more reliable, and has been widely adopted by frontier labs. However, adoption in the outside community has been slow because it's so hard to implement. One of the biggest challenges when adapting RL to a new task is the need for a task-specific "reward function" (way of measuring success). This is often difficult to define, and requires either high-quality labeled data and/or significant domain expertise to generate. RULER is a drop-in reward function that works…
2025 · openpipe.ai · its alternatives →
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✨ Fully autonomous AI Agent that can perform complicated tasks and projects using terminal, browser, and editor. - semanser/codel
2024 · github.com · its alternatives →
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Single-agent LLMs suck at long-running complex tasks. We’ve open-sourced a multi-agent orchestrator that we’ve been using to handle long-running LLM tasks. We found that single LLM agents tend to stall, loop, or generate non-compiling code, so we built a harness for agents to coordinate over shared context while work is in progress. How it works: 1. Orchestrator agent that manages task decomposition 2. Sub-agents for parallel work 3. Subscriptions to task state and progress 4. Real-time sharing of intermediate discoveries between agents We tested this on a Putnam-level math problem, but the…
Feb 2026 · github.com · its alternatives →
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We recently started to use agents to update some documentation across our codebase on a weekly basis, and everything quickly turned into cron jobs, logs, and terminal output. it worked, but was hard to tell what agents were doing, why something failed, or whether a workflow was actually progressing. We thought it would be more interesting to treat agents as long-lived workers with state and responsibilities and explicit handoffs. Something you can actually see and reason about, instead of just tailing logs. So we built Clawe, a small coordination layer on top of OpenClaw that lets agent…
Feb 2026 · github.com · its alternatives →
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I am working on this because I am always afraid of building things that people don't actually want. I let agents role-play analysis the idea, quote and debate with each other. Still working on the output quality, every feedback is priceless. Pls try it out!
Jan 2026 · idea-council.com · its alternatives →
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Argmin AI▲32Hey, HN community! We've built Argmin AI after shipping LLM features where the demo worked, then the bill and latency got unpredictable in production. Prompts expanded, context grew, retrieval got noisy, retries appeared, and agent workflows added loops. Argmin AI optimizes LLM-related expenses as a system: 1. prompt and context efficiency 2. model selection and routing 3. RAG inefficiencies and caching opportunities 4. agent workflows (tool calls, retries, loop control) Changes are validated with evals and guardrails (tests, gates, judges), tailored to your quality definition and goals.…
Jul 2026 · argminai.com · its alternatives →
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Bleenk▲41I kept running into the same issue whenever starting a new project: the setup phase consumed more time than the actual feature work. Preparing boilerplate, restructuring directories, performing refactors, resolving dependency conflicts, and wiring framework logic consistently took hours before I could write meaningful code. Even with modern tooling, the early-stage workload was nearly identical across projects. To remove that bottleneck, I built Bleenk, an AI coding agent that operates directly on real repositories. Instead of generating isolated snippets, it performs multi-step…
Jan 2026 · bleenk.app · its alternatives →
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The context manager and skills library for marketing teams
Apr 2026 · promptr.ai · its alternatives →
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I'm an "ideas person" who messes around with AI on a low budget. I got tired of watching my tokens vanish and context windows filling up while agents fumbled around trying to find the right thing. Agents don't flail like they used to with shell tools, but there are still weak/blind spots and back-and-forth episodes — especially when using tools in combination/sequence. So I built "tilth" today. Or rather, AI built it — every line is Opus 4.6. I spent a lot of my precious tokens getting it to "not shit" (at least several of the different vendors' AI overlords assure me it's not…
Feb 2026 · github.com · its alternatives →
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Excited to share a project I’ve been building for months! Would love to receive honest feedback :) My motivation: AI is clearly going to be the interface for data. But earlier attempts (text-to-SQL, etc.) fell short — they treated it like magic. The space has matured: teams now realize that AI + data needs structure, context, and rules. So I built a product to help teams deliver “chat with data” solutions fast with full control and observability (agent tracing, quality scores, etc) — am I wrong? The product allows you to connect any LLM to any data source with centralized context…
2025 · github.com · its alternatives →
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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →