标签：#plugins

How I automated my content distribution with a DSH plugin I scaffolded myself Posting is easy. Posting everywhere, consistently, is the hard part. I wanted a single command that takes one markdown article and pushes it to Dev.to, GitHub (as a gist), and eventually Bluesky and Mastodon — without my ever touching those web editors again. So I built it as a plugin for DSH (DeepSeek Harness) , using a scaffolding tool that I published myself. Here's the story, the 3 pitfalls that cost me the most time, and how you can get the same thing running in about a minute. Why automate distribution at all? Writing in public is the cheapest compounding asset a developer has. But cross-posting manually has two failure modes: You skip platforms — the "I'll do it later" tab that stays open forever. You lose the content graph — each platform becomes a silo with a slightly different version. A plugin that accepts content + title + [platforms] and returns per-platform status + links removes both. One source, many destinations, audited every time. What I built A DSH content-automation plugin ( dsh-crosspost ) with: Platform adapters : Dev.to (real), GitHub gist (real), Bluesky + Mastodon (stubs, next milestone). BYOK credentials : your tokens live in your DSH profile config — never in code, no platform approval needed from the plugin author. Error classification : every adapter wraps HTTP in try/catch and returns auth / rate-limit / bad-request instead of a raw stack trace, so an agent can decide to retry or skip per platform. Parallel orchestration : one platform failing never blocks the others. The 3 pitfalls that cost me the most time 1. The stale latest dist-tag (the big one) npm install @deepseek-ai/dsh-tools gives you a stale 0.0.1-rc.1 — the real line lives under the next tag. Wasted an evening debugging failures that were purely "wrong version resolved." Lesson: check dist-tags before installing anything in a fast-moving young ecosystem ( npm view pkg dist-tags ). 2. Pure ESM + b

Over the last while I've built integrations for three places where people work with text and images: Obsidian , VS Code, and Figma. Doing a few of them back to back, I noticed something you don't see from a single one. They're all desktop apps. For your integration to exist at all, the person first installs a program on their machine, and then, inside it, your plugin. You're not writing for the web. You're writing code locked inside someone else's app — and each app has its own runtime, its own rules, and its own wall for you to walk into. The web trained us to think an HTTP request is one line. Inside someone else's sandbox, it turns out even that has to be earned. Figma was the strictest host of the three. I'll tell it through Figma, because it's locked down tighter than Obsidian or VS Code, and everything shows up on it at once. The task was almost comically simple: select a frame, write a caption, pick your social accounts, publish — without exporting the image and opening a second app. We already had the publishing API, so I expected the Figma side to be small. And it was: the main plugin file is 120 lines. The work wasn't in them. It was around them. Figma gives you bytes, not a file The first version came together easily. When the selection changes, the plugin checks whether there's one exportable node and tells the UI what it found. For the preview it exports a small copy; for publishing, separately, at 2×. const bytes = await nodes [ 0 ]. exportAsync ({ format : " PNG " , constraint : { type : " SCALE " , value : 2 }, }); 2× because the image still has a journey ahead of it: social networks recompress what you upload, and small text on a design goes noticeably softer by the time it lands in a feed. Then the first quirk of the foreign house. Figma hands the plugin not a file but raw PNG bytes — exportAsync() returns a Uint8Array . Our normal API won't eat that — it doesn't take a giant image stuffed into a JSON body. It creates a post first, hands the client

Block, Inc. describes migrating ~450 JVM repositories into a monorepo across Cash App and Square engineering to reduce dependency drift and coordination overhead. The system supports ~8,800 weekly builds with ~10 min p90 CI time. The approach improves cross-service changes, build visibility, and developer experience through dependency graph–based builds, selective CI, and custom IDE tooling. By Leela Kumili