Open source · Free to try

Turn your git history into
a feature risk map

Know exactly which parts of your codebase are accumulating technical debt — without Jira, without integrations, without config. Just point it at any git repo.

Get early access → ⭐ Star on GitHub
$
pip install faultline
faultline analyze . --llm --src src/
Analyzing: /path/to/my-app
~ 1,240 commits in range → ~18 sec
Found 1,240 commits over 365 days
Found 312 files under src/
Import graph: 312 files → 9 clusters
Merging & naming features with Claude...
Claude merged → 6 features
Detected 6 features
 
Features by Risk
Feature Health Commits Bug Fixes Bug %
payments 23 112 38 33.9%
auth 54 48 12 25.0%
dashboard 91 67 2 3.0%
 
Saved: .faultline/feature-map-20260302-143221.json

You know you have tech debt.
You just don't know where.

Engineering managers make refactoring decisions based on gut feeling. faultline gives you the data.

🔥

Bugs keep coming from the same place

Every sprint, the same features generate support tickets. You can feel it — but you can't prove it to leadership without hard data.

🗂️

Jira doesn't reflect reality

Tickets are inconsistently tagged. Some engineers label everything "bug fix," others don't. Your tooling is only as good as your process.

🧭

Planning refactoring blindly

You want to invest in paying down tech debt, but without a risk map you're guessing which features actually need attention.

👤

Bus factor hiding in plain sight

One engineer owns the payments feature. Nobody else knows it. faultline surfaces knowledge concentration before it becomes a crisis.

From git log to risk map
in under a minute

No integrations. No account setup. Just one command.

01

Point at any git repo

Run faultline analyze . in any project directory. No setup, no config files, no account.

02

Git history is analyzed

faultline reads commit messages, changed files, and authors across the past year. Bug fixes are detected automatically by commit message patterns.

✓ Analysis complete
Feature risk map
✗ payments 23
! auth 54
✓ notifications 78
✓ dashboard 91
↳ checkout-flow
↳ refund-flow
03

Features detected automatically

Import graph clustering groups files by how they connect. With --llm, Claude maps clusters to business domains — no folder naming conventions required.

You get actionable risk data

A health score per feature (0–100), bug fix ratio, commit trends, and optional flow breakdown — saved as JSON and printed to your terminal.

Everything you need.
Nothing you don't.

Zero configuration

No YAML files, no account creation, no integrations. Run one command in any git repository and get results immediately. Works on any language — JavaScript, Python, Go, Rust.

faultline analyze .
🧠

AI-powered feature detection

Uses import graph clustering to find connected modules, then Claude (or a local Ollama model) maps them to business features — "payments", "auth", "dashboard" — not technical folders.

--llm --provider anthropic|ollama
📊

Health scores per feature

Every feature gets a 0–100 health score based on its bug fix ratio and commit activity. Instantly see which features are critical (red), watch (yellow), and healthy (green).

health = 100 − bug_ratio × 200
🔀

User-facing flow detection

Go deeper than features. With --flows, faultline breaks each feature into named user journeys — checkout-flow, refund-flow — each with their own risk score.

--llm --flows
Built for real engineering teams

<60s

Average analysis time on
a 1,000-commit repo

$0

Cost to analyze public
and open source repos

~$0.001

Typical Claude API cost
per repo with --llm

100%

Private — your code never
leaves your machine with Ollama

Be first to know when
the SaaS launches

The CLI is free and open source today. The SaaS — with dashboards, GitHub App integration, and team collaboration — is coming soon.

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