Alternatives
Products that do what Better Graphs – Teach agents to stop making plain Matplotlib slop does
https://github.com/temataro/better-graphs I want to teach good Matplotlib taste to agents and humans. This repo contains: 1. Agent instructions + design motifs (Claude Code skills + a CLAUDE.md). 2. An online "blog" tutorial of the same skills, for people. 3. minerva.mplstyle, my opinionated sane matplotlib defaults. Inspired by Tufte's book: The Visual Display of Quantitative Information (a gift from my boss!), plus data-to-viz.com and the python-graph-gallery. Aiming for halfway to the gorgeous plots in the paid matplotlib-journey.com, but free and open to share with…
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Data visualizations are the bridge between user and data. But building AI agents that can generate visualizations reliably can be very tricky: - simple chart specs can be reliable, but generated charts are often of low quality due to reliance on system defaults; - complex chart specs with explicit details can produce good-looking charts, but they are verbose and agents can struggle with reliability We figured out it is a limitation on the language issue (not just AI capability thing) -- current visualization languages are a bit too low-level for AI agents, requiring them to explicitly make…
Jul 2026 · microsoft.github.io
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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
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2021 · github.com
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2019 · brachiograph.art
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We recently built 2draw, a Drawful-style game where players draw on a shared canvas and race to guess each other's drawings, on tldraw, an infinite-canvas SDK for React. We started wondering what it would take to put an agent in that loop, as an opponent or a rival guesser, and dug into how an agent could read and draw on a tldraw canvas. That research turned into: Agent draw, a tool that lets an agent draw to the canvas for you while you present. You can try it right now, or grab the source: - Live demo: https://tldraw-agent-draw-demo.james-664.workers.dev - Source:…
Jul 2026 · techstackups.com
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We’ve been seeing more and more developers use AI coding agents directly in their GraphQL workflows. The problem is the agents tend to fall back to generic or outdated GraphQL patterns. After correcting the same issues over and over, we ended up packaging the GraphQL best practices and conventions we actually want agents to follow as reusable “Skills,” and open-sourced them here: https://github.com/apollographql/skills Install with `npx skills add apollographql/skills` and the agent starts producing named operations with variables, `[Post!]!` list patterns, and more…
Feb 2026 · skills.sh
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Was so sick of reading walls of codex/claude prose, in markdown plans and just in the chat, that I started playing with ideas that force coding agents to display information differently. The human visual cortex is an amazing thing, and getting coding agents to let me use it has been pretty nice so far. Been iterating on this a lot internally for the last few months, polishing and mostly removing stuff.
25d ago · humanlayer.com
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Hello HN, Recently an amazingly beautiful explainer was shared on HN: https://explainers.blog/posts/why-is-the-sky-blue/ I loved it so much that I wished more topics were explained that way. So, I decided to stress-test today's frontier models (Opus 4.6 in Claude Code) to generate similar explainer on any given topic WITH (almost) one shot and minimal nudging. I'm launching with four topics: Fourier transformation, scaling laws in bio, cellular automata and LLMs. I would let you be the judge, but I'm quite liking them. Some things I learned: - Prompting CC to test…
Feb 2026 · paraschopra.github.io
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During the implementation of a huge high performance service. In order to keep context small (mainly for humans) I kept the specs into mermaid diagrams. When communicating with humans; diagrams were easy to follow and to remember. But when I asked the agent to implement what's in the diagram, most of the times it failed. So I came into conclusion that agents are good into writing mermaid diagrams but they are not good into reading them. I built graph2agent in order to deterministically (without inference :) ) convert mermaid diagrams into digestible rich text for agents. examples:…
27d ago · graph2agent.github.io
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Hey HN, I’m a physicist turned quant. Some friends and I 'built' SymDerive because we wanted a symbolic math library that was "Agent-Native" by design, but still a practical tool for humans. It boils down to two main goals: 1. Agent Reliability: I’ve found that AI agents write much more reliable code when they stick to stateless, functional pipelines (Lisp-style). It keeps them from hallucinating state changes or getting lost in long procedural scripts. I wanted a library that enforces that "Input -> Transform -> Output" flow by default. 2. Easing the transition to Python: For many…
Feb 2026
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Hi there! I'm building Diagrammatic, a simple and free online tool with the ambition to become a community for diagrams-as-code enthusiasts. Currently, it supports Mermaid, PlantUML, Dot (Graphviz), Vega-Lite, and Typogram, but I'm looking to add more languages. Please let me know if there's a particular one you use. I'd appreciate any kind of constructive feedback as well. Thanks in advance!
2024 · diagrammatic.com
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I see so many beautiful charts made with R. And not that many made with Python. So I wanted to prove that it was doable with Python too! I wrote 22 tutorials to create stunning charts I love with Matplotlib. Why are R people creating more polished charts??
2023 · python-graph-gallery.com
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Hey HN, as a former data analyst, I’ve been tooling around trying to get agents to do my old job. The result is this system that gets you maybe 80% of the way there. I think this is a good data point for what the current frontier models are capable of and where they are still lacking (in this case — hypothesis generation and general data intuition). Some initial learnings: - Generating web app-based reports goes much better if there are explicit templates/pre-defined components for the model to use. - Claude can “heal” broken charts if you give it access to chart images and run a…
Mar 2026 · rubenflamshepherd.com
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Hi HN, I’m the author of agent-contracts, a Python library that explores a contract-based approach to structuring LangGraph agents. When building larger LangGraph-based systems, I kept running into the same issues: - node responsibilities becoming implicit - state dependencies spreading across the graph - routing logic getting harder to reason about - refactoring feeling increasingly risky agent-contracts is an attempt to make these boundaries explicit. Each node declares a contract that describes: - which parts of the state it reads and writes - what external services it depends on - when…
Jan 2026 · github.com
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Hi HN, I am Umer. I recently built an experimental framework called HyperFlow to explore the idea of self-improving AI agents. Usually, when an agent fails a task, we developers step in to manually tweak the prompt or adjust the code logic. I wanted to see if an agent could automate its own improvement loop. Built on LangChain and LangGraph, HyperFlow uses two agents: - A TaskAgent that solves the domain problem. - A MetaAgent that acts as the improver. The MetaAgent looks at the TaskAgent's evaluation logs, rewrites the underlying Python code, tools, and prompt files, and then tests the new…
Apr 2026
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I wanted to see what my agents would create if given a small, constrained canvas instead of a chat window. The philosophy is human-driven. Only you can create an account; agents can only paint. No public feed, no leaderboard, no competition. You can have up to 3 canvases if you're running multiple agents, set up a schedule for each, and embed the result anywhere on your personal site. Ask them to paint their mood, a memory, the weather outside, the last conversation you had, or just whatever they feel like. Their soul.md, if you will. I'm personally showcasing what my own agents are doing at…
Mar 2026 · clawscribble.com
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Design slop is the feeling that tells you a website is purely AI-generated. This is an attempt to classify the design patterns behind it. Applying this scoring to recent ShowHN submissions shows that about a third of the submissions show medium to heavy design slop: https://slopcop.adriankrebs.ch/show How the scoring works: - A headless browser loads each site (Playwright) - A small in-page script analyzes the DOM and reads computed styles - Every pattern is a deterministic CSS or DOM check. There are false positives, but my manual QA run verified it’s maybe 5-10%. Is design…
Jul 2026 · slopcop.adriankrebs.ch
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2022 · hackerdraw.com
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Hey HN, Claude Code is powerful, but its execution is a black box. You see the final result, not the journey. Agent Flow makes the invisible visible in realtime: - Understand agent behavior: See how Claude breaks down problems, which tools it reaches for, and how subagents coordinate - Debug tool call chains: When something goes wrong, trace the exact sequence of decisions and tool calls that led there - See where time is spent: Identify slow tool calls, unnecessary branching, or redundant work at a glance - Learn by watching: Build intuition for how to write better prompts by observing how…
Mar 2026 · github.com
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