AI · alternatives · 2026
24 alternatives to Facts
I had a lot of issues with spec-driven approaches, agents are too readily producing fluff, large projects have so many specs agents start making mistakes maintaining them. There's a constant consistency tax. In the end every spec is just a bunch of facts, so I decided to leave that and throw away everything else while making it friendlier for agentic use. Introducing facts - skills and CLI for agents to use facts-driven development. https://github.com/av/facts
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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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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When we asked developers from large engineering teams, almost everyone is using Claude Code, Cursor, or Copilot. But adoption is still inconsistent. Some of us would have 15 agents running in Claude Code at the same time; some would still refuse to use any of them and write code manually. There's a fragmented AI development problem: - Five developers building similar features, and all of them start from scratch - No way to share "here's how we prompt AI to follow our architecture" - No trail of how the AI changes were generated - People leave the company, so does the their knowledge Aviator…
2025 · aviator.co · its alternatives →
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Deep Work Plan▲114Models matter. Context matters more. Give your agent a plan.
Jun 2026 · deepworkplan.com · its alternatives →
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Cognitorafree▲86Built a multi-agent research system with OpenAI Agents SDK where specialized AI agents collaborate autonomously: Master Orchestrator → Data Analyst → Statistician → Report Writer Each agent has specific expertise. The orchestrator delegates tasks. All agents can execute code securely to solve problems. Example workflow: "Analyze e-commerce data" - Data Analyst: writes Python to load/clean data, spots trends - Statistician: performs significance tests, calculates growth rates - Report Writer: synthesizes findings into executive summary This demonstrates OpenAI Agents SDK's handoff system…
2025 · cognitora.dev · its alternatives →
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Skills with 210k GitHub Data & Translate/Refine &Benchmark
Mar 2026 · skills-refiner.com · 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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Spec27▲34Hi HN! We’re a team of ML validation specialists and we’ve been building /Spec27, a tool for testing whether AI agents still do their job safely and reliably as models, prompts, tools, and surrounding systems change. We started working on this because a lot of current LLM evaluation work seems aimed at scoring general model behavior, while many teams are deploying systems that have a specific mission to fulfill. Many of the tools also assume you have full access to the agent stack and traces so you can place SDKs and Gateways, but a lot of agents are being created on vendor platforms…
Apr 2026 · spec27.ai · its alternatives →
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We now write most of our code with agents. For a while, PRs piled up, causing review fatigue, and we had this sinking feeling that standards were slipping. Consistency is tough at this volume. I’m sharing the solution we found, which has become our main product. Continue (https://docs.continue.dev) runs AI checks on every PR. Each check is a source-controlled markdown file in `.continue/checks/` that shows up as a GitHub status check. They run as full agents, not just reading the diff, but able to read/write files, run bash commands, and use a browser. If it finds…
Feb 2026 · docs.continue.dev · its alternatives →
- 9
Hey HN, we built an Econ+Finance database to let AI agents do investment research. We spend a lot of tokens to organize macro releases and SEC filings into a clean format, so that your agents have more context to do actual analysis. The problem AI agents are great at data analysis. But they become ineffective if most of their context window is spent on gathering and cleaning data, instead of validating hypotheses. Data in the wild is messy and rarely standardized. Definitions and measurements change over time. This problem is compounded by a fragmented data universe. Point solutions exist…
Jul 2026 · github.com · its alternatives →
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GitHub: https://github.com/ClioAI/kw-sdk Most AI agent frameworks target code. Write code, run tests, fix errors, repeat. That works because code has a natural verification signal. It works or it doesn't. This SDK treats knowledge work like an engineering problem: Task → Brief → Rubric (hidden from executor) → Work → Verify → Fail? → Retry → Pass → Submit The orchestrator coordinates subagents, web search, code execution, and file I/O. then checks its own work against criteria it can't game (the rubric is generated in a separate call and the executor never sees it…
Feb 2026 · github.com · its alternatives →
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Your AI has your code's text, never its map. Fix that.
Jun 2026 · luuuc.github.io · its alternatives →
- 12SD
Spec Driven Development approach allows to squeeze more from coding agents thanks to few strong concepts: - decomposition across two dimensions. first you generate specs in multiple steps (requirements, code analysis, design), than you split task into multiple subtasks and implement them one by one - you clear context between every step - after spec generation and after subtask implementation. this helps keep cost low and context clear and focused which boost performance - specs written to disk help with information persistency - delivering specs layer by layer help to catch early when agent…
May 2026 · its alternatives →
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Research-grounded, harness-agnostic skills for AI coding agents - SteveVitali/agent-skills
Aug 2026 · github.com · its alternatives →
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Contribute to getcalx/oss development by creating an account on GitHub.
Mar 2026 · github.com · its alternatives →
- 15CF
Hi HN, I built my first project using an LLM in mid-2024. I've been excited ever since. But of course, at some point it all turns into a mess. You see, software is an intricate interwoven collection of tiny details. Good software gets many details right; and does not regress as it gains functionality. My bootstrapped startup, ApprovIQ (https://approviq.com) is trying to break into a mature market with multiple fully featured competitors. I need to get the details right: MVP quality won't sell. So I opted for Test-Driven Development, the classic red/green/refactor. Writing…
Feb 2026 · codeleash.dev · its alternatives →
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Hey HN, I've made a groundbreaking discovery: procrastination can lead to questionable projects! While avoiding real work, I somehow created a directory of 130+ AI agents and frameworks. It's like I tried to organize a robot party and everyone showed up. What's inside: - A list of AI agents - Frameworks to build more agents So, HN, before I spiral into an existential crisis: did I accidentally create something useful, or should I go touch grass? P.S. If this somehow becomes the next big thing, I promise to pretend it was intentional all along.
2024 · aiagentsdirectory.com · its alternatives →
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Excited to launch Awesome AI Agent Skills! An open-source collection of 70+ production-ready skills to make your AI agents smarter and faster. Stop reinventing the wheel. From code generation to security audits, it's all here. Contributions welcome! Let's build together.
Feb 2026 · github.com · its alternatives →
- 181D
We just open-sourced the internal system we built at Assembled for running coding agents as a team. Coding agents worked well for individual engineers, but the surrounding workflow was a bit of a mess. We generally found that many engineers had different MCP connections and context for their agents, personal automations running that other people couldn’t access, and very little introspection for what a human’s input into the coding agent looked like. So we built an internal system that converted coding agents into shared team infrastructure. The system runs Codex, Claude Code, OpenCode, and…
Jun 2026 · its alternatives →
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The Problem "Vibing" with LLMs is often too shallow for complex logic, while writing full specifications is cognitively expensive and slow. We need a middle ground that mimics how human programmers gather context—scanning structure before diving into details. The Solution: Outline Driven Development (ODD) I've built a "batteries-included" kit for Gemini/Claude/Codex that uses AST analysis to understand code structure rather than just raw text. This relies on a hyper-optimized Rust toolchain (`ast-grep`, `ripgrep`, `jj`, etc.) to feed precise, structural context to the agent. 1. The…
Nov 2025 · github.com · its alternatives →
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I built SpecMind, an open source developer tool for spec driven vibe coding. It keeps architecture and implementation aligned from the first commit instead of letting them drift apart. With AI assistants writing more of our code, projects move faster but architectural consistency is often lost. Each developer or AI can introduce new patterns, and after a few sprints, the structure becomes fragmented. SpecMind helps prevent that by generating and maintaining living architecture specs directly from your code. It works in three steps: 1. analyze – scans your codebase and generates…
Nov 2025 · github.com · its alternatives →
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I’ve spent the past 10 years working on AI in finance, with much of that time focused on building evaluation systems for production environments. As agents become more widely adopted, more software engineering and product people have start building them. But I’ve noticed that many teams are not yet fluent in systematic evaluation, or in the processes needed to keep agent quality high over time. For large organizations, that gap is rarely the bottleneck due to dedicated teams. But after speaking with a number of startups, it became clear that building strong, up-to-date evals is much harder…
May 2026 · github.com · its alternatives →
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789 skills & 10 autonomous agents for Claude Code
Mar 2026 · clskillshub.com · its alternatives →
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Enables small-to-large self-hosted ai models to use local source code when running tool-calling agentic workloads. We actively data mine 20,900+ (2+ TB) popular github repos using large and small ai models to create reuseable: json, markdown and parquet files for local-first tool-calling models. - d
May 2026 · github.com · its alternatives →
- 24
Hi HN folks, I have been building AI agents for quite some time now. The shift has gone from LLM + Tools → LLM Workflows → Agent + Tools + Memory, and now we are finally seeing true agency emerge: agents as systems composed of tools, command-line access, fine-grained system capabilities, and memory. This way of building agents is powerful, and I believe it is here to stay. But the real question is: are the systems powering these agents ready for that future? I do not think so. Using Docker for a single agent is not going to scale well, because agents need to be lightweight and fast. LLMs…
Mar 2026 · 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 →