开发者
I Built a Discord Server Discovery Platform
I Started Building a Discord Server Directory I’ve spent a lot of time around Discord communities, and one thing has always bothered me. Finding a good Discord server is harder than it should be. There are thousands of communities for gaming, anime, roleplay, technology, social groups and pretty much every niche you can think of. But finding the right one usually means jumping between invite links, old posts, server lists and search results. At some point I thought, why not build a better way to discover them? That’s how I started working on Dizord. The first version was pretty simple. I wanted a place where a server could be listed, people could discover it, and everything could be organized around interests instead of just one giant list of servers. Then the project started getting bigger. More servers meant more categories and tags. More tags meant better search and filtering. Server information changes constantly, so keeping listings updated became another problem to solve. I’m building the backend with Laravel and working with the Discord API to handle server information and synchronization. There are also a lot of small things behind the scenes that aren't obvious when you simply open a server listing page. One of the things I'm currently working on is making discovery better for smaller communities. A server shouldn't need tens of thousands of members just to be discoverable. The goal is pretty simple: Make it easier to find a Discord community you'll actually want to stay in. The project is still evolving, but the current version is live: https://dizord.com I'm still experimenting with search, categorization, server activity and ways to make a large directory useful instead of overwhelming. If you're building a directory, marketplace, or any project with thousands of constantly changing pages, I'd also be interested in hearing how you handle discovery and indexing at scale.
AI 资讯
AI isn’t enough to protect social media communities from AI
Why humans need to moderate humans.
开发者
Stop Writing Cover Letters From Scratch: How I Automated the Most Annoying Part of Job Hunting
Job hunting is exhausting. Between tweaking resumes, updating portfolios, and filling out endless...
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Building an AI lineup optimizer for a Discord esports bot (the algorithm, not the hype)
Every esports team captain has done this by hand at least once: open Discord, scroll through a dozen "I can play Thursday after 8" messages, cross-reference them against who plays Tank versus DPS, remember that one of your DPS is actually a sub, and try to assemble a starting five that can actually scrim tonight. It takes fifteen minutes, you get it slightly wrong, and you do it again the next day. I build Supatimer , a free Discord bot for competitive gaming teams, and "generate the lineup for me" was the single most requested feature. This post is about how the lineup optimizer actually works, why it is genuinely AI (and not in the marketing sense), and where a large language model fits in versus where it absolutely does not. "AI" is doing a lot of work in this industry Half the Discord bots on the market slapped "AI" on their landing page the week ChatGPT launched. Usually it means there is a chatbot command somewhere that proxies to an LLM. That is fine, but it is not what your team needs when it is 7:45pm and you have a scrim at 8. There are two honest definitions of AI worth separating: Search and optimization - the classical branch. Constraint satisfaction, combinatorial optimization, planning. This is the part of AI that solves "given these rules and these resources, find the best valid arrangement." Machine learning / LLMs - the statistical branch. Pattern recognition, generation, extraction from unstructured text. The lineup problem is squarely a problem for the first kind. So that is what I built first. The lineup problem, stated precisely Strip away the gaming context and a lineup is a constrained assignment problem: You have N players , each with a set of roles they can fill (Tank, DPS, Support, IGL, and so on). Each player has an availability signal for a given time block (available, maybe, unavailable). Each player has a roster status (starter, substitute, trial). The game defines a required composition : Overwatch 2 wants 1 Tank, 2 DPS, 2 Support. Va
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Discord admits AI moderation bug wrongfully banned users over harmless images
The company confirmed that the issue had been affecting accounts since May, with an additional 200 users banned over the weekend before its team identified and fixed the problem.
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I put my Claude Code sessions on Discord — and now it's a one-line plugin
About 7,000 developers install a little tool of mine every month. It has 7 GitHub stars. I think about that gap a lot — but it also means thousands of these cards are quietly running in Discord right now, which is the whole point. It's called claude-rpc , and as of today you can install it from inside Claude Code itself. What it is claude-rpc is a small Node daemon that takes the lifecycle events Claude Code already fires — session start, each tool call, token counts — and turns them into a live Discord Rich Presence card on your profile: current model, project, what tool is running, plus lifetime stats. Your friends see what you're building; you get a year heatmap of your own work. It's free, open source, and has zero runtime dependencies — the Discord IPC client is hand-rolled, so the entire supply chain fits in a single review. The new part: a Claude Code plugin Two lines, in the editor: /plugin marketplace add rar-file/claude-rpc /plugin install claude-rpc@claude-rpc The card shows up on your next session. That's it. The plugin itself is deliberately thin — one SessionStart hook that runs the same installer you'd run by hand ( npx claude-rpc@latest setup ) once, in the background, then gets out of the way. Claude Code measures it at ~0 tokens of context per session. The real package still does the real work: wiring hooks, holding Discord's local socket, starting at login. It's now the fifth way to install the same tool — npx , a curl one-liner, Homebrew, a Windows exe, and now this — so pick whatever fits your setup. How it actually works No magic: 5 hooks, one small state file, and a daemon that holds Discord's local socket. No polling, no network calls, no telemetry you didn't opt into. If you want to read it, start with src/discord-ipc.js . Try it Site + build log: https://claude-rpc.vercel.app Source: https://github.com/rar-file/claude-rpc Built solo, on weekends. If one of those 7,000 cards ends up being yours, a GitHub star is the cheapest possible way to
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Building a Kaggle Competition Notification Bot
I built a tool called "kaggle-dingdong" that automatically fetches Kaggle competition information and sends notifications to Email, Slack, and Discord. It runs daily on a schedule via GitHub Actions, and you get notified whenever a new competition is published. https://github.com/asherish/kaggle-dingdong Why I Built This Checking the Kaggle competitions page every day is tedious. Featured competitions in particular have entry deadlines, so missing them means losing the opportunity. While RSS feeds and official notification features exist, I wanted notifications delivered directly to the channels I actually use (Discord and Slack), so I built my own. Tech Stack Python 3.13 uv — Package manager and build tool (by Astral) Kaggle Python SDK v2.0.0 — Fetching competition info GitHub Actions — Automated daily execution at 09:00 UTC pytest — Testing Three notification channels are supported: Channel Method Format Email SMTP HTML (card layout) Slack Incoming Webhook Block Kit Discord Webhook Rich Embed Architecture GitHub Actions (cron: daily at 09:00 UTC) ↓ Fetch competition list via Kaggle API ↓ Filter by conditions in config.json ↓ Compare with sent history to extract unnotified competitions ↓ Send notifications to configured channels ↓ Update sent history (max 200 entries) The project structure is as follows: kaggle-dingdong/ ├── src/kaggle_dingdong/ │ ├── __main__.py # Entry point │ ├── config.py # Configuration loading │ ├── competitions.py # Fetch & filter competitions from Kaggle API │ ├── email_sender.py # Email notifications │ ├── slack_sender.py # Slack notifications │ ├── discord_sender.py # Discord notifications │ └── history.py # Sent history management ├── tests/ # pytest tests ├── config.json # Filter configuration └── .github/workflows/ └── notify.yml # GitHub Actions workflow Implementation Highlights Fetching and Filtering Competitions The Kaggle SDK is used to fetch the competition list. In addition to the default sort order, it also fetches with recentl