codeclone 2.0.2

A structural review layer for Python — baseline-aware, deterministic, built for CI and AI agents

CodeClone adds a control layer between analysis and CI: it isolates structural regressions from historical debt, so merges are blocked only by what actually got worse.

The same analysis pipeline powers CLI reports, CI checks, the MCP server, and native IDE/agent clients — so humans and AI agents operate on identical, deterministic facts.

• Documentation: https://orenlab.github.io/codeclone/
• Live sample report: https://orenlab.github.io/codeclone/examples/report/
• Source: https://github.com/orenlab/codeclone
• Issues: https://github.com/orenlab/codeclone/issues

Features

Control & governance

• Baseline governance — separates accepted legacy debt from new regressions; CI fails only on what changed
• CI-first — deterministic output, stable ordering, exit code contract, pre-commit support
• Reports — interactive HTML, JSON, Markdown, SARIF, and text from one canonical report

Detection & analysis

• Clone detection — function (CFG fingerprint), block (statement windows), and segment (report-only) clones
• Structural findings — duplicated branch families, clone guard/exit divergence, and clone-cohort drift
• Quality metrics — cyclomatic complexity, coupling (CBO), cohesion (LCOM4), dependency cycles, adaptive depth profile, dead code, health score, and overloaded-module profiling
• Adoption & API — type/docstring annotation coverage, public API surface inventory and baseline diff
• Coverage Join — fuse external Cobertura XML into the current run to surface coverage hotspots and scope gaps
• Security Surfaces — report-only inventory of security-relevant capability boundaries without vulnerability claims

Surfaces & integrations

• MCP control surface — triage-first agent and IDE interface over the same canonical pipeline; read-only by contract
• IDE & agent clients — VS Code extension, Claude Desktop bundle, and Codex plugin over the same MCP contract

Performance

• Fast — incremental caching, parallel processing, warm-run optimization

Quick Start

uv tool install codeclone

codeclone .                    # analyze
codeclone . --html             # HTML report
codeclone . --html --open-html-report
codeclone . --json --md --sarif --text
codeclone . --ci               # CI mode

Run without installing:

uvx codeclone@latest .

CI Workflow

# 1. Generate and commit the baseline
codeclone . --update-baseline

# 2. Enforce it in CI
codeclone . --ci

--ci equals --fail-on-new --no-color --quiet. When a trusted metrics baseline is loaded, CI mode also enables --fail-on-new-metrics.

Exit codes:

Contract errors (2) take precedence over gating failures (3).

Reports

codeclone . --html
codeclone . --json
codeclone . --md
codeclone . --sarif
codeclone . --text

All formats are rendered from one canonical report payload.

Report contract: https://orenlab.github.io/codeclone/book/08-report/

MCP and Native Clients

uv tool install "codeclone[mcp]"

codeclone-mcp --transport stdio

The MCP server is read-only by contract: it never mutates source files, baselines, cache, or repository state.

MCP docs: https://orenlab.github.io/codeclone/book/20-mcp-interface/

Configuration

[tool.codeclone]
baseline = "codeclone.baseline.json"
min_loc = 10
min_stmt = 6
block_min_loc = 20
block_min_stmt = 8
fail_on_new = true
fail_cycles = true
fail_dead_code = true
fail_health = 80

Precedence: CLI flags > pyproject.toml > built-in defaults.

Config reference: https://orenlab.github.io/codeclone/book/04-config-and-defaults/

License

• Code: MPL-2.0 (LICENSE)
• Documentation and docs-site content: MIT (LICENSE-MIT)

License scope map: https://github.com/orenlab/codeclone/blob/main/LICENSES.md