Black Box Unlock Mischief. Mayhem. Merge conflicts. Exposed. Code forensics tool based on Adam Tornhill's "Your Code as a Crime Scene". The useful bit from code-forensics research is concentration: 2-8% of files cause 60-90% of defects. Black Box Unlock gives AI coding agents those signals through MCP tools and a Claude Code plugin.

For agents (MCP + plugin)

uv tool install black-box-unlock   # provides bbu and bbu-mcp

Register the MCP server in Claude Code (.mcp.json):

{ "mcpServers": { "black-box-unlock": { "command": "bbu-mcp" } } }

Tools: get_hotspots, get_file_forensics, get_coupled_files, get_ownership, get_ci_failures, get_flaky_steps, xray_file, review_change. The CI tools return status and errors, so a missing or partial GitHub response cannot look like a clean result. Failed-run data includes the workflow, run URL, commit, time, and paths changed in that commit. Those paths are implicated by the failed run, not proven to have caused it.

The Claude Code plugin in this repo adds /review-change, /analyze, /hotspots, a git-forensics agent, and an ambient coupling guard that warns when you edit one half of a repeatedly coupled file pair. The hook parses Claude's JSON directly and does not require jq. Install it via the self-hosted marketplace:

/plugin marketplace add michael-denyer/black-box-unlock
/plugin install black-box-unlock@black-box-unlock

Both bbu and bbu-mcp must be on PATH for the plugin and MCP server to work.

CLI

Installation

uv pip install -e .

analyze-repo uses the gh CLI for CI data by default; pass --no-ci to skip it. review-change queries GitHub only when a profile or --include-ci turns that signal on.

Usage

# Analyze last 30 days of git history, output JSON
bbu analyze-repo --days=30

# Generate interactive HTML report
bbu analyze-repo --days=30 --output=html > report.html

# Adjust coupling detection threshold (default 0.3)
bbu analyze-repo --min-coupling=0.5 --output=html > report.html

# Skip CI failure analysis (faster, no GitHub access needed)
bbu analyze-repo --no-ci --output=html > report.html

# Analyze a different repository
bbu analyze-repo --repo /path/to/repo --output=html > report.html

# Per-function churn for one file (Tornhill's X-Ray)
bbu xray src/hot_file.py --days 365

# Review branch commits and local work from the upstream merge base
bbu review-change --base origin/main

# Review only staged work, or only unstaged and untracked work
bbu review-change --staged
bbu review-change --working-tree

# Use a named .bbu.toml profile and retain failed workflow details
bbu review-change --profile release

# Diagnose local activation (CI and gh remain optional)
bbu doctor

Project configuration

Add .bbu.toml when the built-in path roles or review defaults do not fit the repository:

default_profile = "release"

[[path_roles]]
pattern = "app/**/*.vue"
role = "source"

[[path_roles]]
pattern = "snapshots/**"
role = "generated"

[profiles.release]
days = 180
min_coupling = 0.4
min_shared_revisions = 3
include_ci = true
max_actions = 3

Project path rules run in file order before the built-in rules. Named profiles set review defaults; command-line and MCP arguments override the selected profile. Invalid configuration stops the review with a clear error. The full format and glob rules are in docs/CONFIGURATION.md.

Features

Does the ranking actually predict bugs?

Measured with bbu validate (split-history: rank hotspots on the older half, count bug-fix commits in the newer half): median Spearman rho 0.46 across six real repos (click, flask, pydantic, rich, fastapi, httpx); the top 10% of ranked files attracted a median 46% of subsequent bug-fix touches; uniform would be 10%. Method, per-repo numbers, and limitations: docs/VALIDATION.md.

bbu validate --repo /path/to/repo --days 730

HTML report

The HTML output is a self-contained investigation workspace:

• Files - searchable, sortable metrics with a persistent evidence panel
• Risk matrix and change landscape - two routes into the same selected file
• Coupling evidence - confidence-first pairs with support and denominators
• CI and signals - collection status, failed runs, flaky steps, and policy

The report opens in Code only scope: source files and migrations, with coupling limited to pairs whose two endpoints are in that scope. Tests, configuration, documentation, generated files, and repository metadata remain available through the scope selector.

Numeric evidence columns use proportional heat bars scaled to the current scope. The change landscape groups files by code area without repeating low-information repository path levels.

Pinned ECharts and Tabulator assets are embedded in the document, so opening a saved report makes no CDN requests. Charts are supplementary: the evidence needed to interpret them remains in keyboard-operable grids and text panels.

flowchart LR
    Git[Git History] --> Analyze[bbu analyze-repo]
    CI[GitHub Actions] --> Analyze
    Analyze --> JSON[JSON Output]
    Analyze --> HTML[HTML Report]
    HTML --> Grid[Searchable Evidence]
    HTML --> Matrix[Risk Matrix]
    HTML --> Treemap[Repository Map]

Architecture

See docs/ARCHITECTURE.md for full details.

src/black_box_unlock/
├── cli.py              # Typer CLI
├── complexity.py       # Indentation-depth complexity proxy
├── analysis.py         # Orchestration
├── core/               # Pydantic models, exceptions, logging
├── git/                # Churn, coupling, ownership, defects, log extraction
├── cicd/               # CI/CD forensics (build failures, flaky steps via gh CLI)
└── visualization/      # Offline HTML investigation workspace

Development

# Install development dependencies and the Git hook
uv sync --all-extras --dev
uv run prek install

# Run the same quality and security checks as CI
uv run prek run --all-files

# Run tests
uv run pytest -v

# Verbose output for debugging
bbu --verbose analyze-repo

The prek gate covers repository hygiene, Ruff, Pyrefly, GitHub Actions linting, Markdown and link checks, Mermaid rendering, workflow security, and locked-dependency auditing. Link and dependency checks need network access.

License

MIT