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repowiseHexSleeves/tailscale

Repowise · Codebase intelligence

HexSleeves / tailscale

gogithub.com/HexSleeves/tailscale
Indexed atbf7d815·14h ago·Behind upstream
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Files indexed
2.3k
Symbols
25k
Languages
15
Packages
3

Does the health score find the bugs?

Repowise ranks every file by predicted defect risk. Of the 20 files it flags as riskiest, 10 (50%) actually needed a bug fix in the last 6 months — 5.0× better than picking files at random.

Precision
50%
Lift
5.0×
Flagged
20

Languages

  • go89.0%
  • yaml3.1%
  • typescript2.4%
  • markdown2.3%
  • shell1.4%
  • json0.7%
  • swift0.4%

Key modules3

  • web

    client/web

    typescript
  • tsconnect

    cmd/tsconnect

    typescript
  • goexe

    tool/goexe

    makefile

Code health

Full report

How HexSleeves/tailscale works

This page is an auto-generated, always-fresh map of the HexSleeves/tailscale repository, written primarily in go. Repowise indexes the source, parses every symbol, computes a dependency graph, scores per-file code health from complexity, duplication, test coverage and churn, mines git history for hotspots and ownership, and lifts the resulting architectural decisions into a wiki you can read or query through MCP.

The codebase has 2,275 source files, 24,889 symbols, and 15 languages, structured as a monorepo with 3 packages. Git churn analysis flags 160 high-frequency files as hotspots — places where bugs, rewrites, and code review tend to concentrate. The dependency graph clusters into 253 tightly-coupled module communities.

Use the panels above to open the interactive dashboards, or connect this repo to your editor via the Repowise MCP server for grounded answers inside Claude, Cursor, or VS Code.

  • makefile0.2%
  • Explore HexSleeves/tailscale

    Overview

    Files, symbols, languages, packages, git intelligence

    Architecture

    Dependency graph, layered architecture, symbol index, and third-party dependencies

    Code health

    Per-file health scores, hotspots, test coverage, dead code, and refactoring targets

    AI docsPro

    Module-by-module documentation generated from source

    Commits

    Change-risk ranked history with AI-agent provenance and hotspots

    Contributors

    Bus-factor, per-file maintainer maps, and human/agent collaboration

    Decisions

    Architectural decisions extracted from commits and PRs

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    Ask grounded questions over the indexed code

    75/100
    Some risk160 hotspots
    • Code health58
    • Dead code93
    • Hotspot density86
    • Bus factor79