Is this just for engineering or is it being used for other functions, like Marketing and HR as well?

Very interesting about the domain and workflows. Do you think domain could map to a team or is it different?

At your company how are you shipping your assets? How do you do the domain and workflow grouping?

The tool support is certainly one of the key pillars of the project so we're open to any tool additions that will help people get value from the project.

We wanted something short and easy to remember

My main argument is that just using vanilla git where you store it in the directory that the AI coding agent expects means that you can't share across teams or orgs.

Also, not every kind of team is comfortable with git. How would you distribute these assets to a Marketing team?

The short version: sx treats skills, MCP server configs, slash commands, agents, hooks, and rule files as versioned packages. You define them once, push them to a vault (a local folder, a git repo, or our hosted backend), and install them where they belong. There's a lockfile so installs are reproducible, scope levels for org / team / repo / individual, and the CLI translates the same asset into the format each AI client expects.

Supported clients today: Claude Code, Cursor, GitHub Copilot, Cline, Codex, Gemini (CLI / VS Code / JetBrains / Android Studio), Kiro, claude.ai, chatgpt.com. The last two are what let non-engineering teams (marketing, legal, ops) use the same primitive instead of being locked out of the AI-assets ecosystem.

The thing I'd most like feedback on is whether the scope model is the right shape. Org → team → repo → path → individual is what's emerged from talking to ~60 teams over the last six months, but I expect bigger orgs will surface scopes we haven't modeled (sub-team, environment, etc.).

Why this and not just plugins / vendor marketplaces? Claude Code plugins are real and a good step up over raw git-checked-in CLAUDE.md files. The limitations show up at scale: each plugin is scoped to its publishing repo, so teams duplicate skills across plugins, and you're still locked to a single vendor's client. Full writeup with the technical details: https://www.sleuth.io/post/there-s-an-npm-shaped-hole-in-the...

Comments URL: https://news.ycombinator.com/item?id=48151058

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Comments URL: https://news.ycombinator.com/item?id=47756723

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How are you handing distributing your Agent Skills and MCP's? Is this a problem you're seeing?

It was a constant with all that they felt like 2 - 7 percent of their developers had made huge productivity gains but that the rest were not really seeing any, despite having access to the same tools.

We then hit the problem of how to best share these and keep them up to date, especially with multiple repositories. It led us to build sx - https://github.com/sleuth-io/sx, a package manager for AI tools.

For background, Sleuth makes improving engineering efficiency easy and continuous. We started by focusing on tracking DORA metrics to give teams useful insight they can act on to improve (https://news.ycombinator.com/item?id=27974573). We built first-class integrations that span your entire software delivery tech stack, from ticketing and change management all the way through to CI/CD and observability tools.

Now, we’re leveraging that foundation to allow teams to improve engineering efficiency even more rapidly, continuously and easily with automation. We’ve built a bunch of engineering best practices into no-code automations that you can install via a single click from our Automations Marketplace (https://marketplace.sleuth.io/ ). These will help your teams drive improvements across their entire engineering tech stack.

We built this to give software teams the capabilities they’ve always wanted, but that are often too much lift to invest in. We see four key categories of these capabilities:

PR Checks – They’re like linters for your PR process. They let you analyze pull requests to ensure they conform to industry best practices, cutting down review time and improving morale by relieving reviewers of the onus of “policing” best practices.

Notifications – drive awareness, nudge things in the right direction and help teams respond quickly by automatically alerting them when Sleuth determines there’s something they need to know.

Actions – provide a variety of simple, if-this-then-that automations targeted across your software delivery tool chain, that allow you to modify a state in an external system — like automatically transitioning or commenting on a Jira issue to let stakeholders know immediately when a change they care about has deployed to its target environment.

Workflows – provide advanced automations that can evaluate conditions and perform actions across multiple integrated tools. If you’ve ever wanted Slack-based approvals for deploys moving from staging to production, now you have have it with a single click.

We’d love for you to check them all out in our Marketplace and let us know what feedback you have. Thanks in advance!

You can check out Sleuth by going to our website (https://www.sleuth.io ) or better yet, watching us in action in Sleuth (https://app.sleuth.io/sleuth/sleuth/metrics/). Or, you can try our 30-day trial.

Comments URL: https://news.ycombinator.com/item?id=37510140

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We're a series A company, Sleuth makes engineering efficiency measurable and easy to improve. We give teams a complete and accurate view into DORA metrics, insights on where the bottlenecks lie, and tools to automate workflows for efficiency.

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See more details on our open roles via the careers page linked above and you can apply by sending an email with your resume to jobs@sleuth.io