The vital signs of your GitHub repo. Flaky tests, slow reviews, delivery and DORA, risky dependencies and community health, measured in your own GitHub Actions.

_{A tour on demo data. Watch it with sound.}

A free, open-source developer suite for GitHub: CI health and flaky tests, pull request flow, delivery and DORA, dependencies, community health and an org portal. It runs in your own GitHub Actions and keeps its history in your own repo: no StackVitals-hosted backend, account or subscription, and optional integrations use services and keys you choose. GitHub's built-in token covers every module in a repo; an org's private repos in the Portal need a read-only App, and org-wide Copilot usage an org token. Actions minutes on private repos are billed by GitHub as usual (docs/scaling.md). The rules behind its verdicts are checked on public data, with the losses published.

Every run publishes an app on your repo's GitHub Pages (or stackvitals ui owner/repo on your machine): one page per module, decisions and settings saved straight from the browser, setup for more repos in a few clicks once GitHub is connected (connecting takes one token, made from a prefilled GitHub page; Pages are turned on for public repos), and a demo at ?demo=1. docs/app.md walks through it.

Install it as the GitHub Action stackvitals/stackvitals@v0 (also on the GitHub Marketplace), or the CLI and MCP server from PyPI: pip install stackvitals (or run it without installing: uvx stackvitals).

What you see first

When CI fails on a pull request, one comment sorts each failure, from the repo's own CI history:

StackVitals: about this CI failure

1 of 3 failure(s) look like flakes; the rest need a look.

Verdict	What failed	Why
Likely flaky	test t::flaky_one	flaked 6 times in 80 runs in the last 30 days, last 2026-10-20, and the message shows a flake's sign ("TimeoutError"): looks like a flake, check the error, then re-run it
New	test t::new_one	no earlier flakes: likely from this change (fails with "assert result == 2")
Already failing on main	test t::broken_one	also failing on the default branch, not caused by this change

The verdict check still blocks until CI is green: a known flake is re-run, never waved through.

Quick start

pip install stackvitals
gh auth login                        # once, so StackVitals can use your GitHub sign-in
stackvitals init your-name/your-repo

init adds one workflow file to your repo, runs it once and turns on your dashboard:

• Public repo: the dashboard goes live at https://your-name.github.io/your-repo/.

• Private repo: your data stays in your private repo, and the dashboard opens on your machine:

  stackvitals ui your-name/your-repo
  

Just looking? stackvitals ci report owner/repo reports CI health for any public repo in about 20 seconds, with nothing added to it. Prefer clicking? The app's Setup page does the same as init. More: docs/quickstart.md.

How it works

Every step, from what starts a run to what you see: the architecture in detail.

Modules

Stable: measured, reviewed and used on the sandbox for every release. Preview: built and tested, but newer or measured on less; its behaviour may still change.

Works with Jira Cloud, Linear, PagerDuty, incident.io, Copilot usage reports, Slack, Teams, Discord, Discourse, test reports from other CI systems, Backstage, and DevLake's tables (docs/connectors.md). AI agents get every module through one MCP server (11 core tools by default, all 35 with --tools all).

Connect your tools (optional)

Everything works with GitHub's built-in token. Integrations are optional; pass their keys as repository secrets:

- uses: stackvitals/stackvitals@v0
  with:
    webhook: ${{ secrets.SLACK_WEBHOOK }}            # alerts to Slack, Teams or Discord
    pagerduty-token: ${{ secrets.PAGERDUTY_TOKEN }}  # incidents count in DORA
    jira-email: ${{ secrets.JIRA_EMAIL }}            # Jira, with its site URL under
    jira-token: ${{ secrets.JIRA_TOKEN }}            # [connectors.jira] in .github/stackvitals.toml

Every input: docs/install.md. Every setting: docs/settings.md.

AI agents (MCP)

Your coding agent can ask StackVitals before and while it changes code: is this failure a known flake?, what is blocking PR #123?, who should review this?, is this package safe to add? It answers from your repo's history, with the evidence.

Claude Code:

claude mcp add stackvitals -- uvx stackvitals serve

Claude Desktop, Cursor, VS Code and other MCP clients:

{
  "mcpServers": {
    "stackvitals": { "command": "uvx", "args": ["stackvitals", "serve"] }
  }
}

It uses your gh login or GITHUB_TOKEN. The 11 core tools load by default (ci_failure, is_known_flake, pr_queue, who_should_review, check_package, insights and more); stackvitals serve --tools all loads all 35. Listed in the MCP registry as io.github.stackvitals/stackvitals.

Three things it gets right that others get wrong

Measured on public repos beside the rules other tools use (docs/accuracy.md):

• Where you deploy from. With no setup, StackVitals named the right deployment source for 53 of 60 repos (30 of 35 held out). On the same 60, DevLake's default pattern got 9 and a pattern a user would typically write got 22. A wrong source makes every DORA number wrong.
• Who answered an issue. Of the first comments by non-maintainers that the github/issue-metrics action counts as the answer, 46% are drive-bys (40-52%, held-out repos). StackVitals counts the project's answers: maintainers, regular responders and triagers.
• Whether AI help changed anything. Agents' pull requests look 9 points less likely than people's to be merged by someone else. Compared within the same repo, month and size, the gap is +0.5 points (0.0 to +1.1): most of the raw gap comes from which repos agents work in and the size of their changes.

It publishes what failed too. Of the failures an old rule called safe to re-run, 44% (15 of 34) were caused by the change. The tightened rule still got 13 of 81 held-out calls wrong (16%). A stricter one (a flake's sign in the log, no changed file named) got none of 4 fresh calls wrong, too few to show 5%, so nothing is called safe: likely flakes are re-run, never passed by the check. Each sample was labelled by two model families (Claude and Gemini); no person has audited the labels.

Compared with other tools

What each one does better, what StackVitals does differently, and what was measured side by side (docs/compare):

Learn more

• Five minutes: docs/quickstart.md. Try CI Health on any public repo first (needs uv and gh auth login or a GITHUB_TOKEN): uvx stackvitals ci report owner/repo --days 14 --html ./ci-report.
• By role: engineering managers, maintainers, platform teams.
• Before you rely on it: what each rule does, known limitations, what leaves your repo, threat model, enterprise controls.
• More: FAQ, how it works, roadmap, contributing, code of conduct, governance, security.