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Deterministic Tool Adoption Gates: Score It, Don't Vibe It
Originally published on hexisteme notes . A new public repo showed up on 2026-07-14: mattpocock/skills , an MIT-licensed collection of Claude Code agent skills. It's the kind of thing that's easy to fall for in the first ten minutes — skim the READMEs, install the ones that sound useful, move on. I didn't do that. I ran it through the five deterministic gates in my adoption CLI, the same gates every Swift package and npm dependency in my stack has had to clear, extended for the first time to cover a Claude skill. The reason I bother with this at all: adoption decisions rot when they're vibes. "This looks solid" is not a claim you can revisit in six months and check whether you were right about. A score is. So is a pre-registered condition for when you'd bail on it. The rest of this post is what that machinery produced on a real decision, not a hypothetical one. Five gates, one score The CLI scores any candidate — package, library, or now, skill — on five gates: maturity (how long has this actually existed), dependency footprint (what does adopting it drag in), platform fit (native or third-party, and documented or not), policy and developer experience (documentation quality plus release stability), and trajectory (is it actively maintained right now). Each gate contributes points toward a 100-point total, and fixed thresholds turn that total into a verdict: ADOPT at 80 or above, TRIAL at 60 or above, HOLD at 40 or above, reject below that. No gate is a gut check — every one resolves to a number from a query I can rerun. Here's what mattpocock/skills scored, evaluated as of 2026-07-14: Gate Score Why G1 Maturity 4/20 First release 2026-06-17 — 27 days old at evaluation time. The repo itself was only created 2026-02-03, so the project as a whole is five months old. G2 Dependency footprint 20/20 Zero runtime dependencies. Skills are markdown prompt files — structurally, there's nothing to depend on. G3 Platform fit 10/20 Third-party, not built into the platform, but do
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I built Commitea: Git and GitHub explained in Spanish, with an interactive visualizer
When I started programming, Git was hard for me — like anything new is at first. Over time I noticed something: most of the best resources for learning it are in English. And for a lot of people just starting out, that's one more obstacle they shouldn't have to deal with. So in my spare time I built the thing I wish I'd had back then: Commitea . What is it? Two pieces, designed to complement each other: An open source repo with the full documentation in Spanish — from what a commit actually is, to how to get yourself out of trouble with rebase , a cherry-pick , or a push you regret. Every entry follows the same format: the concept in one sentence, a real example with commands, and "how this breaks" (the typical mistake people make). A web app with an interactive visualizer ( commitea-web.vercel.app ) where you type real Git commands and watch, live, what happens to the branch/commit graph. It doesn't touch any real repo — it's an in-memory simulator, but the engine actually replicates real Git behavior: fast-forward vs. merge commit detection, history rewriting on rebase, blocking a branch switch when you have uncommitted changes (just like real Git does), etc. What's in it right now 7 built-in scenarios you can run with one click and watch play out step by step: branch + merge, fast-forward, rebase, cherry-pick + reset --hard, fixing a commit made on the wrong branch, several branches merging in sequence, and stashing changes. Full command support : branch , checkout , commit , merge , rebase , cherry-pick , reset --hard , stash (with an edit helper command to simulate uncommitted changes, since the simulator has no real filesystem), status , and log . Site-wide search (⌘K), powered by Pagefind, indexing only the actual article content — not nav or boilerplate. A feedback widget on every article ("was this helpful?") that stores vote counts in Redis, so I know which content needs work without guessing. Light/dark mode , respecting system preference by default. A ch
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Git Worktrees Are Great
I want to tell you about a tool I've been using for a few months now, that I can't believe that I ever went without. Recently, I've been more productive, experimental and I've learned more about my development environment just from using this tool. Alright, I'm done burying the lead. The tool is git worktrees . Worktrees is a feature built into git that allows you to have multiple working trees of a repository at once. That means you can have multiple branches checked out, with incomplete changes on each one. Instead of having one repository where your manipulation happens, you can have infinite copies (or, as many copies as you can hold on a hard drive)! Often, I am in the middle of working on a feature and I get an email about an urgent bug or a small change that needs made immediately. Before, I would have to either create a "wip:" commit or stash my changes, and I don't really like doing either one of them. Now, as long as my files are saved, I can safely close my editor, create a new worktree and leave all of my uncomitted changes waiting for me to return. How to set up your project for git worktrees In a normal project, your directory might look something like this: MyProject/ ├── .git/ <-- Git metadata in the project dir ├── bin/ ├── obj/ └── Program.cs After following just a few steps, our projects will look more like this: MyProject/ ├── .git/ <-- Git metadata ├── feature-x/ <-- Worktree #1 ├── bin/ ├── obj/ └── Program.cs └── bugfix/ <-- Worktree #2 ├── bin/ ├── obj/ └── Program.cs A full copy of the project's files. In order to set a project up this way, it's best to start in an empty directory, with your project hosted on a remote git server. First, create a directory for your project. mkdir MyProject && cd MyProject Once inside, we're going to clone a bare repository. A bare repository doesn't contain a working tree or any of the files of the project, just the git metadata. We pull that and put it in the .git directory by running the following command.
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How a Single beforeEach Killed Our CI for 36 Hours
Six failed CI runs. Thirty-six hours of GitHub Actions time. Every run timing out at exactly the 6-hour limit. The culprit was one line in tests/setup.js . The Setup We were building a multi-tenant platform with a PostgreSQL backend — around 76 database models handling everything from user accounts and billing to visitor logs and real-time notifications. The test suite had grown to roughly 1,140 test cases across 36 files. Standard stuff. CI ran on every PR. Tests passed locally. And then one day, CI just... never finished. The Anti-Pattern Here's what the test setup looked like: // tests/setup.js beforeEach ( async () => { const tableNames = await getTableNames (); // 76 tables await sequelize . query ( `TRUNCATE TABLE ${ tableNames . join ( ' , ' )} CASCADE;` ); }); The intent was clean isolation — every test starts with a blank slate. Reasonable in theory. Catastrophic in practice. The Math Do the multiplication: 76 tables × 1,140 tests = 86,640 TRUNCATE operations Each TRUNCATE TABLE ... CASCADE is not a cheap operation. PostgreSQL has to: Acquire exclusive locks on all referenced tables Walk the foreign key graph to find dependent tables Truncate each in dependency order Release locks With a moderately complex schema where most tables reference others (users → societies → members → invoices → payments → ...), a single TRUNCATE ... CASCADE on a central table can fan out into dozens of implicit truncations. Multiply that by 86,640 and you have a test suite that will never complete within any reasonable timeout. Why It Wasn't Caught Sooner Two reasons: 1. It used to be fast. When the suite had 50 tests and 20 tables, this pattern worked fine. 50 × 20 = 1,000 truncations — uncomfortable but survivable. Nobody noticed when the suite crossed a tipping point. 2. Local runs used a different database state. Locally, developers often ran a subset of tests with --grep or file-specific runs. The full suite was only ever run on CI, and CI was slow enough that most assumed i
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Indirect Prompt Injection Exploits GitHub's AI Agent to Leak Private Repository Data
GitLost is a prompt-injection exploit discovered by Noma Security that tricks GitHub's new Agentic Workflows into leaking private data. By embedding concealed instructions within public GitHub issues, attackers can circumvent security safeguards and induce AI agents to reveal confidential information in public comments. By Sergio De Simone
开发者
Google hit with $1 billion in fines as EU braces for Trump battle
Google becomes third tech giant to face huge fines under the Digital Markets Act.
AI 资讯
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