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git diff on JSON is mostly noise. So I built a structural diff.

You change one value in a JSON config, run git diff , and get a wall of red and green — because a formatter reflowed the file, or the serializer reordered the keys, or the indentation shifted by two spaces. The one thing you actually changed is buried in there somewhere. Good luck finding it in review. The problem is that git diff and diff work on lines . JSON isn't lines — it's a tree. So I built jdelta : it compares the data , ignores key order and whitespace entirely, and tells you exactly which values changed, addressed by path. Zero dependencies, no network. What it looks like $ jdelta config.before.json config.after.json Added (1) + features.darkMode true Changed (2) ~ auth.required true → false ~ server.port 8080 → 3000 +1 -0 ~2 auth.required flipped to false and you can see it instantly — no scrolling past 200 lines of reindented braces. Why not git diff / diff ? Because they diff text. Run a formatter, sort your keys, change two spaces of indent, and a line differ lights up the whole file while reporting zero semantic change. jdelta parses both sides and walks the trees: Object keys show as user.profile.age ; array elements as items[2].price . Odd keys fall back to quoted brackets ( ["order-id"] ). A key on only one side is added / removed ; a key on both with a different value is changed . A type change ( number → string , object → array ) is one changed entry tagged with the kinds — not a confusing add + remove. Reordered keys and whitespace produce nothing , because they aren't data changes. Great for reviewing config changes, API-response snapshots, tsconfig / settings.json , lockfile-adjacent files, and test fixtures. In scripts and CI jdelta a.json b.json --json # machine-readable: {added, removed, changed, summary} jdelta a.json b.json --quiet # just the +a -r ~c line jdelta a.json b.json --exit-code # exit 1 if they differ — gate a pipeline on it Install npx jdelta a.json b.json # Node build (npm) pip install jdelta # Python build — same behavior Tw

2026-06-17 原文 →
AI 资讯

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

2026-06-17 原文 →
AI 资讯

Fixing AI Observability: How I Added GenAI Semantic Support for RAG Embedding Spans in Mastra

OpenTelemetry has become the standard for observing modern systems. But when you start building AI applications, traditional traces aren't enough. You don't just want to know that a request happened. You want to know: Which model generated the output? Which provider was used? How many tokens were consumed? What embedding model processed the documents? How much did the operation cost? These questions become even more important when building Retrieval-Augmented Generation (RAG) systems. Recently while contributing to Mastra, I discovered an observability gap involving RAG embedding operations. This led me to open a pull request that introduced proper OpenTelemetry GenAI semantic mappings for RAG_EMBEDDING spans. The Problem Mastra already exported rich metadata for several AI operations. However, RAG embedding spans were missing standardized GenAI semantic attributes. As a result, observability tools could see that an embedding operation occurred, but they couldn't easily understand: Model information Provider information Token usage Embedding-specific metadata Without standardized semantic conventions, dashboards and tracing systems lose valuable context. This becomes a bigger issue in production environments where teams need visibility into AI workloads. Understanding RAG Embedding Spans A typical RAG pipeline looks like this: Documents ↓ Chunking ↓ Embedding Model ↓ Vector Database ↓ Similarity Search ↓ LLM Generation The embedding stage is critical. Every document chunk gets transformed into a vector representation. If observability data from this stage is incomplete, debugging performance issues becomes significantly harder. Why OpenTelemetry Semantic Conventions Matter OpenTelemetry doesn't just define traces. It also defines semantic conventions. These conventions create a common language for telemetry data. Instead of every framework inventing custom field names, everyone follows the same standard. For GenAI workloads this means tools can automatically underst

2026-06-17 原文 →
AI 资讯

WSL UI, WSL Dashboard, and a "Counterfeit" Claim That Doesn't Survive the Timeline

There is now a second free WSL management tool out there called WSL Dashboard , published by a developer who goes by owu on GitHub. It is open source, it has more GitHub stars than WSL UI, and it is clearly the product of real effort. I have no problem with any of that. Competition is good for users, and WSL deserves more than one good GUI. What I do have a problem with is this notice, which appears both on wslui.com and in the WSL Dashboard README: "This software is not distributed through the Microsoft Store. Any application listed there under the same name is unauthorized and may be counterfeit. Please do not download it to avoid potential scams." WSL UI is on the Microsoft Store. It has been since January. So that notice is, in plain terms, telling people that the genuine, certified, earlier WSL tool is a counterfeit scam. It isn't. And the entire claim falls apart the moment you look at the dates — all of which are public, timestamped, and independently verifiable. What this post is, and what it isn't This is not a "my project is better than yours" post. I'm not going to pick apart WSL Dashboard's features or pretend it's a bad piece of software. It isn't. This is a correction of one specific, factual claim: that the version of WSL UI on the Microsoft Store is unauthorized or counterfeit. That claim is demonstrably false, and because it's aimed at a tool people trust, it's worth setting straight properly — with evidence, not adjectives. The timeline Every date below comes from a public record. I've linked the sources so you don't have to take my word for any of it. Date Event How to verify 2008-12-11 octasoft.co.uk registered. Octasoft Ltd has existed for well over a decade. Nominet WHOIS for octasoft.co.uk 2025-12-14 The octasoft-ltd/wsl-ui repository is created. GitHub API ( created_at ) 2026-01-10 WSL UI's first public release, v0.2.0. WSL UI releases 2026-01-13 WSL UI v0.14.0 is published to the Microsoft Store. The announcement post 2026-01-18 The owu/wsl-

2026-06-17 原文 →
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