open source v-.-.-

humancov

See it in action

One command. Full visibility.

terminal

$ humancov scan

AI-Provenance Scan
==================
Total files scanned:  42
AI-generated:         28
Human-written:        10
Mixed:                2
Unknown (no header):  2

Of AI files:
  Reviewed:  21 / 28  (75%)
  Tested:    8 / 28  (29%)

How it works

Three steps. No config.

Add provenance headers

Add headers to the top of your files. Works with 30+ languages automatically.

# AI-Provenance-Origin: ai

# AI-Provenance-Reviewed: false

click to copy

Scan your repo

Run the command and get a full report. Binaries and ignored paths are skipped automatically.

$ humancov scan click to copy

Review and track

Review AI code, set Reviewed: true. Everything updates automatically.

AI Tools

Teach your AI to tag its code.

Run humancov init to detect your AI tool config files and inject provenance instructions automatically.

CLAUDE.md

Claude Code

.cursorrules

Cursor

.windsurfrules

Windsurf

copilot-instructions.md

GitHub Copilot

terminal

$ humancov init

  done: CLAUDE.md (Claude Code instructions added)
  done: .cursorrules (Cursor instructions added)
  skip: .windsurfrules (already has AI-Provenance instructions)

2 file(s) updated.

Install

Ready in seconds.

npm install -g humancov click to copy

Requires Node >= 18. Zero config. Single dependency.

Spec

Header keys.

Key	Required	Values	Description
`AI-Provenance-Origin`	yes	`ai` `human` `mixed`	Who wrote the file
`AI-Provenance-Generator`	no	free-text	Tool used (claude-code, copilot...)
`AI-Provenance-Reviewed`	yes	`true` `false` `partial`	Human review status
`AI-Provenance-Tested`	no	`true` `false` `partial`	Human test status
`AI-Provenance-Confidence`	no	`high` `medium` `low`	Reviewer confidence
`AI-Provenance-Notes`	no	free-text	Any context

Languages

30+ file types supported.

JS, TS, JSX, TSX, Java, C, C++, C#, Go, Rust, Swift, Kotlin, Scala, Dart, PHP, Groovy

Python, Ruby, Shell, YAML, TOML, Perl, R, PowerShell, Dockerfile, Terraform, Elixir, Julia

<!--

HTML, XML, SVG, Vue, Svelte, Markdown

/* */

CSS, SCSS, Less

SQL, Lua, Haskell, Elm

Badge

Show your review coverage.

12%

< 25% - needs review

48%

25-74% - in progress

82%

75-99% - mostly reviewed

100%

100% - fully reviewed

terminal

$ humancov scan --badge

https://img.shields.io/badge/human--reviewed-75%25%20of%20AI%20files-green

![Human Reviewed](https://img.shields.io/badge/human--reviewed-75%25...)

Enforce in your pipeline.

# .github/workflows/provenance.yml
name: AI Review Check
on: [push, pull_request]
jobs:
  check:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: actions/setup-node@v4
      - run: npx humancov scan --check 80

Fails your build if not enough AI code has been human-reviewed.

CLI

All commands.

terminal

$ humancov scan            # scan repo, print report
$ humancov scan --json     # output as JSON
$ humancov scan --badge    # shields.io badge URL
$ humancov scan --check 80 # CI gate: fail if < 80%
$ humancov manifest        # generate .humancov file
$ humancov init            # add instructions to AI tool configs