kimun 0.34.3

Code metrics tool — health score, complexity, duplication, hotspots, ownership
kimun-0.34.3 is not a library.

Kimün (km)

Kimün means "knowledge" or "wisdom" in Mapudungun, the language of the Mapuche people.

The mascot is Madu, a pudú who is a machi: the one who holds the knowledge of her people. She is the sister of Kalku, the mascot of kalku.

Website: kimun.tools · Also in Spanish.

New to Kimün? Watch Madu explain it in two minutes — the grade, the metrics, what git remembers, the impact of a change and the gate for CI.

A fast command-line tool for code analysis, written in Rust. Run km score on any project to get an overall health grade (A++ to F--) across five quality dimensions — cognitive complexity, duplication, indentation depth, Halstead effort, and file size — with a list of the files that need the most attention.

Note: This repository is not the same as the Rust console note-taking app kimun by nico2sh. That project is available at https://github.com/nico2sh/kimun.

Beyond the aggregate score, Kimün provides 17 specialized commands:

  • Static metrics — lines of code by language (cloc-compatible), duplicate detection (Rule of Three), Halstead complexity, cyclomatic complexity, cognitive complexity (SonarSource), indentation complexity, two Maintainability Index variants (Visual Studio and verifysoft), code smell detection, and a comprehensive multi-metric report.
  • Git-based analysis — hotspot detection (change frequency × complexity, Thornhill method), code churn (pure change frequency), code ownership / knowledge maps via git blame, temporal coupling between files that change together, impact of a diff (diffusion and missing co-changes), per-author ownership summary, and file age classification (Active / Stale / Frozen).
  • AI-powered analysis — optional integration with Claude to run all tools and produce a narrative report.

Installation

cargo install kimun              # from crates.io
brew install lnds/kimun/kimun    # with Homebrew, on macOS and Linux

Either one installs the km binary. There are also ready-made binaries for macOS, Linux and Windows on the releases page. From a checkout of this repository, cargo install --path . builds it from source.

Shell completions

Generate and install a completion script for your shell:

# zsh
km completions zsh > ~/.zfunc/_km
# add to ~/.zshrc if not already present:
#   fpath=(~/.zfunc $fpath)
#   autoload -Uz compinit && compinit

# bash
km completions bash > /etc/bash_completion.d/km

# fish
km completions fish > ~/.config/fish/completions/km.fish

Commands

km loc -- Count lines of code

km loc [path]

Run on the current directory:

km loc

Run on a specific path:

km loc src/

Options:

Flag Description
-v, --verbose Show summary stats (files read, unique, ignored, elapsed time)
--by-author Break down lines of code by git author (requires a git repository)
--format {table,json,short,terse} Output format (default: table)

Example output:

────────────────────────────────────────────────────────────────────
 Language                Files        Blank      Comment         Code
────────────────────────────────────────────────────────────────────
 Rust                        5          120           45          850
 TOML                        1            2            0           15
────────────────────────────────────────────────────────────────────
 SUM:                        6          122           45          865
────────────────────────────────────────────────────────────────────

km dups -- Detect duplicate code

Finds duplicate code blocks across files using a sliding window approach. Applies the Rule of Three: duplicates appearing 3+ times are marked as CRITICAL (refactor recommended), while those appearing twice are TOLERABLE.

Test files and directories are excluded by default, since tests often contain intentional repetition.

km dups [path]

Options:

Flag Description
-r, --report Show detailed report with duplicate locations and code samples
--show-all Show all duplicate groups (default: top 20)
--min-lines N Minimum lines for a duplicate block (default: 6)
--include-tests Include test files in analysis (excluded by default)
--max-duplicates N Exit with code 1 if duplicate groups exceed this limit (--max-duplicates 0 fails on any duplicate)
--max-dup-ratio PERCENT Exit with code 1 if the duplicated-lines ratio exceeds this percentage (e.g. --max-dup-ratio 5.0)
--fail-on-increase REF Exit with code 1 if the current duplication ratio is higher than at the given git ref (e.g. origin/main). Prevents debt from growing silently in CI
--format {table,json,short,terse} Output format (default: table)

Example summary output:

────────────────────────────────────────────────────────────────────
 Duplication Analysis

 Total code lines:                                             3247
 Duplicated lines:                                              156
 Duplication:                                                  4.8%

 Duplicate groups:                                               12
 Files with duplicates:                                           8
 Largest duplicate:                                        18 lines

 Rule of Three Analysis:
   Critical duplicates (3+):     7 groups,    96 lines
   Tolerable duplicates (2x):    5 groups,    60 lines

 Assessment:                                                    Good
────────────────────────────────────────────────────────────────────

Example detailed output (--report):

────────────────────────────────────────────────────────────────────
 [1] CRITICAL: 18 lines, 3 occurrences (36 duplicated lines)

   src/parser.rs:45-62
   src/formatter.rs:120-137
   src/validator.rs:89-106

 Sample:
   fn process_tokens(input: &str) -> Vec<Token> {
       let mut tokens = Vec::new();
       for line in input.lines() {
       ...

────────────────────────────────────────────────────────────────────
 [2] TOLERABLE: 12 lines, 2 occurrences (12 duplicated lines)

   src/main.rs:100-111
   src/cli.rs:200-211

 Sample:
   match result {
       Ok(value) => {
       ...
────────────────────────────────────────────────────────────────────

Excluded test patterns

By default, km dups skips files matching common test conventions:

  • Directories: tests/, test/, __tests__/, spec/
  • By extension: *_test.rs, *_test.go, test_*.py, *.test.js, *.spec.ts, *Test.java, *_test.cpp, and more

Use --include-tests to analyze test files as well.

km indent -- Indentation complexity

Measures indentation-based complexity per file: standard deviation of indentation depths and maximum depth. Higher stddev suggests more complex control flow.

km indent [path]

Options:

Flag Description
--format {table,json,short,terse} Output format (default: table)
--include-tests Include test files in analysis (excluded by default)

km hal -- Halstead complexity metrics

Computes Halstead complexity metrics per file by extracting operators and operands from source code.

km hal [path]

Metrics

Symbol Metric Formula Description
n1 Distinct operators -- Unique operators in the code
n2 Distinct operands -- Unique operands in the code
N1 Total operators -- Total operator occurrences
N2 Total operands -- Total operand occurrences
n Vocabulary n1 + n2 Size of the "alphabet" used
N Length N1 + N2 Total number of tokens
V Volume N * log2(n) Size of the implementation
D Difficulty (n1/2) * (N2/n2) Error proneness
E Effort D * V Mental effort to develop
B Bugs V / 3000 Estimated delivered bugs
T Time E / 18 seconds Estimated development time

Higher effort, volume, and bugs indicate more complex and error-prone code.

Options:

Flag Description
--format {table,json,short,terse} Output format (default: table)
--include-tests Include test files in analysis (excluded by default)
--top N Show only the top N files (default: 20)
--sort-by METRIC Sort by effort, volume, or bugs (default: effort)

Example output:

Halstead Complexity Metrics
──────────────────────────────────────────────────────────────────────────────
 File                      n1   n2    N1    N2    Volume     Effort   Bugs
──────────────────────────────────────────────────────────────────────────────
 src/loc/counter.rs       139  116  3130  1169   34367.7   24070888  11.46
 src/main.rs               37   43   520   185    4457.0     354743   1.49
──────────────────────────────────────────────────────────────────────────────
 Total (2 files)                     3650  1354   38824.7   24425631  12.95

Supported languages

Rust, Python, JavaScript, TypeScript, Go, C, C++, C#, Java, Objective-C, PHP, Dart, Ruby, Kotlin, Swift, Shell (Bash/Zsh).

km cycom -- Cyclomatic complexity

Computes cyclomatic complexity per file and per function by counting decision points (if, for, while, match, &&, ||, etc.).

km cycom [path]

Options:

Flag Description
--format {table,json,short,terse,github,codeclimate} Output format (default: table). github emits GitHub Actions annotations; codeclimate (alias: gitlab) emits CodeClimate JSON for GitLab Code Quality
--include-tests Include test files in analysis (excluded by default)
--top N Show only the top N files (default: 20)
--min-complexity N Skip files whose most complex function is below N; with --per-function, also hide functions below N (default: 1)
--per-function Show per-function breakdown

km cogcom -- Cognitive complexity

Computes cognitive complexity per file and per function using the SonarSource method (2017). Unlike cyclomatic complexity, cognitive complexity measures how difficult code is to understand, penalizing deeply nested structures and rewarding linear control flow.

km cogcom [path]

Options:

Flag Description
--format {table,json,short,terse,github,codeclimate} Output format (default: table). github emits GitHub Actions annotations; codeclimate (alias: gitlab) emits CodeClimate JSON for GitLab Code Quality
--include-tests Include test files in analysis (excluded by default)
--top N Show only the top N files (default: 20)
--min-complexity N Skip files whose most complex function is below N; with --per-function, also hide functions below N (default: 1)
--per-function Show per-function breakdown
--sort-by METRIC Sort by total, max, or avg (default: total)

In brace languages a function ends where its braces balance. A body introduced by = (fn f(x) = expr, as in Kaikai, Kotlin or Scala) has no closing brace of its own: it runs while its braces are open and the following lines are indented deeper than the declaration. km cycom finds functions the same way.

km mi -- Maintainability Index (Visual Studio variant)

Computes the Maintainability Index per file using the Visual Studio formula. MI is normalized to a 0–100 scale with no comment-weight term.

km mi [path]

Formula

MI = MAX(0, (171 - 5.2 * ln(V) - 0.23 * G - 16.2 * ln(LOC)) * 100 / 171)

Where V = Halstead Volume, G = cyclomatic complexity, LOC = code lines.

Thresholds

MI Score Level Meaning
20–100 green Good maintainability
10–19 yellow Moderate maintainability
0–9 red Low maintainability

Options:

Flag Description
--format {table,json,short,terse} Output format (default: table)
--include-tests Include test files in analysis (excluded by default)
--top N Show only the top N files (default: 20)
--sort-by METRIC Sort by mi (ascending), volume, complexity, or loc (default: mi)

Example output:

Maintainability Index (Visual Studio)
──────────────────────────────────────────────────────────────────────
 File                       Volume Cyclo   LOC     MI  Level
──────────────────────────────────────────────────────────────────────
 src/loc/counter.rs        32101.6   115   731    0.0  red
 src/main.rs               11189.6    16   241   17.5  yellow
 src/loc/report.rs          6257.0    13   185   22.2  green
──────────────────────────────────────────────────────────────────────
 Total (3 files)                         1157   13.2

km miv -- Maintainability Index (verifysoft variant)

Computes the Maintainability Index per file. MI combines Halstead Volume, Cyclomatic Complexity, lines of code, and comment ratio into a single maintainability score.

This is the verifysoft.com variant, which includes a comment-weight term (MIcw) that rewards well-commented code.

km miv [path]

Formula

MIwoc = 171 - 5.2 * ln(V) - 0.23 * G - 16.2 * ln(LOC)
MIcw  = 50 * sin(sqrt(2.46 * radians(PerCM)))
MI    = MIwoc + MIcw

Where V = Halstead Volume, G = cyclomatic complexity, LOC = code lines, PerCM = comment percentage (converted to radians).

Thresholds

MI Score Level Meaning
85+ good Easy to maintain
65–84 moderate Reasonable maintainability
<65 difficult Hard to maintain

Options:

Flag Description
--format {table,json,short,terse} Output format (default: table)
--include-tests Include test files in analysis (excluded by default)
--top N Show only the top N files (default: 20)
--sort-by METRIC Sort by mi (ascending), volume, complexity, or loc (default: mi)

Example output:

Maintainability Index
────────────────────────────────────────────────────────────────────────────────
 File                       Volume Cyclo   LOC  Cmt%   MIwoc      MI  Level
────────────────────────────────────────────────────────────────────────────────
 src/loc/counter.rs        32101.6   115   731   3.6   -16.2     2.8  difficult
 src/main.rs                8686.7    14   204  14.6    34.5    68.2  moderate
 src/util.rs                2816.9    18    76   9.5    55.4    84.7  moderate
────────────────────────────────────────────────────────────────────────────────
 Total (3 files)                         1011                  51.9

km hotspots -- Hotspot analysis

Finds hotspots: files that change frequently AND have high complexity. Based on Adam Thornhill's method ("Your Code as a Crime Scene").

km hotspots [path]

Formula

Score = Commits × Complexity

Files with high scores concentrate risk — they are both change-prone and complex, making them the highest-value refactoring targets.

By default, complexity is measured by total indentation (sum of logical indentation levels across all code lines), following Thornhill's original method from "Your Code as a Crime Scene". Use --complexity cycom for cyclomatic complexity instead.

Requires a git repository. Merge commits are excluded from the count.

Options:

Flag Description
--format {table,json,short,terse} Output format (default: table)
--include-tests Include test files in analysis (excluded by default)
--top N Show only the top N files (default: 20)
--sort-by METRIC Sort by score, commits, or complexity (default: score)
--since DURATION Only consider commits since this time (e.g. 30d, 6m, 1y)
--complexity METRIC indent (default, Thornhill) or cycom (cyclomatic)

Duration units: d (days), m (months, approx. 30 days), y (years, approx. 365 days).

Example output (default — indentation complexity):

Hotspots (Commits × Total Indent Complexity)
──────────────────────────────────────────────────────────────────────────────
 File                    Language Commits Total Indent      Score
──────────────────────────────────────────────────────────────────────────────
 src/main.rs                 Rust      18        613      11034
 src/loc/counter.rs          Rust       7       1490      10430
 src/dups/detector.rs        Rust       7       1288       9016
 src/dups/mod.rs             Rust       9        603       5427
 src/report/mod.rs           Rust       4        998       3992
──────────────────────────────────────────────────────────────────────────────

Score = Commits × Total Indentation (Thornhill method).
High-score files are change-prone and complex — prime refactoring targets.

Example output (--complexity cycom):

Hotspots (Commits × Cyclomatic Complexity)
──────────────────────────────────────────────────────────────────────────────
 File                     Language Commits Cyclomatic      Score
──────────────────────────────────────────────────────────────────────────────
 src/loc/counter.rs           Rust       7        115        805
 src/dups/mod.rs              Rust       9         44        396
 src/main.rs                  Rust      18         21        378
 src/cycom/analyzer.rs        Rust       4         92        368
 src/dups/detector.rs         Rust       7         46        322
──────────────────────────────────────────────────────────────────────────────

Score = Commits × Cyclomatic Complexity.
High-score files are change-prone and complex — prime refactoring targets.

km knowledge -- Code ownership analysis

Analyzes code ownership patterns via git blame (knowledge maps). Based on Adam Thornhill's method ("Your Code as a Crime Scene" chapters 8-9).

km knowledge [path]

Identifies bus factor risk and knowledge concentration per file. Generated files (lock files, minified JS, etc.) are automatically excluded.

Risk levels

Risk Condition Meaning
CRITICAL 1 person owns >80% High bus factor risk
HIGH 1 person owns 60-80% Significant concentration
MEDIUM 2-3 people own >80% combined Moderate concentration
LOW Well-distributed Healthy ownership

Knowledge loss detection

Use --since to define "recent activity". If the primary owner of a file has no commits in that period, the file is flagged with knowledge loss risk. Use --risk-only to show only those files.

Options:

Flag Description
--format {table,json,short,terse} Output format (default: table)
--include-tests Include test files in analysis (excluded by default)
--top N Show only the top N files (default: 20)
--sort-by METRIC Sort by concentration, diffusion, or risk (default: concentration)
--since DURATION Define recent activity window for knowledge loss (e.g. 6m, 1y, 30d)
--risk-only Show only files with knowledge loss risk
--summary Aggregate by author: files owned, lines, languages, worst risk
--bus-factor Show project bus factor (minimum contributors covering 80% of code)
--author NAME Show only files owned by this author (case-insensitive substring match)

Example output:

Knowledge Map — Code Ownership
──────────────────────────────────────────────────────────────────────────────
 File                       Language  Lines  Owner         Own%  Contrib  Risk
──────────────────────────────────────────────────────────────────────────────
 src/loc/counter.rs             Rust    731  E. Diaz        94%        2  CRITICAL
 src/main.rs                    Rust    241  E. Diaz        78%        3  HIGH
 src/walk.rs                    Rust    145  E. Diaz        55%        5  MEDIUM
──────────────────────────────────────────────────────────────────────────────

Files with knowledge loss risk (primary owner inactive): 1
  src/legacy.rs (Former Dev)

Use --bus-factor to compute how many contributors you can afford to lose:

$ km knowledge --bus-factor
Project Bus Factor: 2

 Losing 2 key contributors would put 80% of the project's knowledge at risk.
 Risk: HIGH — two people hold critical knowledge

──────────────────────────────────────────────
 Rank  Author        Lines    Share  Cumulative
──────────────────────────────────────────────
    1  E. Diaz        8420   68.12%     68.12%
    2  A. Torres      1490   12.06%     80.18%  ← 80% threshold
    3  R. Soto         940    7.61%     87.79%
──────────────────────────────────────────────

km tc -- Temporal coupling analysis

Analyzes temporal coupling between files via git history. Based on Adam Thornhill's method ("Your Code as a Crime Scene" ch. 7): files that frequently change together in the same commits have implicit coupling, even without direct imports.

km tc [path]

Formula

Coupling strength = shared_commits / min(commits_a, commits_b)

Coupling levels

Strength Level Meaning
>= 0.5 STRONG Files change together most of the time
0.3-0.5 MODERATE Noticeable co-change pattern
< 0.3 WEAK Occasional co-changes

High coupling between unrelated modules suggests hidden dependencies or architectural issues — consider extracting shared abstractions.

Options:

Flag Description
--format {table,json,short,terse} Output format (default: table)
--top N Show only the top N file pairs (default: 20)
--sort-by METRIC Sort by strength or shared (default: strength)
--since DURATION Only consider commits since this time (e.g. 6m, 1y, 30d)
--min-degree N Minimum commits per file to be included (default: 3)
--min-strength F Minimum coupling strength to show (e.g. 0.5 for strong only)

Example output:

Temporal Coupling — Files That Change Together
──────────────────────────────────────────────────────────────────────────────────
 File A                     File B                     Shared  Strength  Level
──────────────────────────────────────────────────────────────────────────────────
 src/auth/jwt.rs            src/auth/middleware.rs          12      0.86  STRONG
 lib/parser.rs              lib/validator.rs                 8      0.53  STRONG
 config/db.yaml             config/cache.yaml                6      0.35  MODERATE
──────────────────────────────────────────────────────────────────────────────────

12 coupled pairs found (3 shown). Showing pairs with >= 3 shared commits.
Strong coupling (>= 0.5) suggests hidden dependencies — consider extracting shared abstractions.

Note: File renames are not tracked across git history. Renamed files appear as separate entries.

km impact -- Impact of a diff

Measures how far a change reaches, for a PR or for uncommitted work, before it is merged.

What the blast radius is

The blast radius of a change is the part of the system that can behave differently because of it, beyond the files it edits. A change to a function is not only that function: it is every piece of code that calls it, and what calls those. If the function's own tests pass and something that uses it breaks in production, the break was inside the radius and outside the tests.

km impact measures it at two levels, and reports what guards it:

Level The radius is Read from
Projects The projects of the repository that depend on the changed ones, directly or through others Manifests
Source files The files that call the functions that changed, and the files that use those The dependency graph of the code

At each level the radius is a count over a total: 3 of 6 projects, 2 of 618 source files. It answers how much of the system to worry about. Next to it comes what is unprotected: the files inside the radius that no test exercises. A wide radius fully covered by tests is a change to make with care; one file in the radius with no test is where it will break without warning, and the report names it.

Two more measures describe the change itself rather than its reach: how spread it is (diffusion), and which files usually change with it and were left out (logical radius).

km impact --since-ref origin/main [path]         # the branch you are on
km impact --since-ref main --until-ref feature   # a branch, without checking it out
git diff main... | km impact --diff -               # a patch
km impact --pr 123                               # a GitHub pull request

What is measured

Source The change History ends at Manifests and files read from
--since-ref REF From where REF and HEAD diverged to the working tree: committed, uncommitted and untracked changes, and deletions That merge base The working tree
--since-ref A --until-ref B What B brings since it diverged from A, whatever is checked out That merge base The tree of B
--diff FILE A patch in git format, from a file or from stdin (-) HEAD, or where --since-ref and HEAD diverged when given The working tree
--pr NUMBER A GitHub pull request As the mode it resolves to As the mode it resolves to

It is always the change over the whole repository: path only locates the repository and does not narrow the analysis. Generated files (lock files, minified assets) are left out of every measure.

--pr requires the GitHub CLI (gh) installed and authenticated. kimun runs it as a program; it links no GitHub client and stores no token.

  • When the repository has the commits of the pull request, it is measured from them, as between two refs. A pull request merged by squash or rebase, whose head was never fetched, is measured from the patch GitHub serves, read against the tree of the commit that merged it. Its base and that commit are not compared: the base may be many merges behind, and everything merged in between would be counted.
  • Otherwise (a pull request from a fork, or one not fetched) its patch is taken from gh pr diff and measured like any other patch, with a note on stderr. git fetch origin pull/NUMBER/head makes its commits available.

A patch (--diff, or a pull request without local commits) is measured against the working tree, where it is not applied:

  • it must be in git format with the a/ and b/ prefixes, as git diff, git format-patch and gh pr diff print it, without colors;
  • for a branch use git diff main... (three dots): git diff main compares against the tip of main, and shows what main gained since as if the branch had undone it. To include uncommitted work, --since-ref main is the direct way;
  • a project the patch creates is not known, so its files have unknown reach, and --affected lists every project;
  • if the patch is already applied in HEAD, pass --since-ref so that its own commits are not counted as history.

Blast radius: projects

Which projects of the repository are reached by the diff. Meant for monorepos, where a change to a shared library reaches applications its author may not know.

A project is a directory with a manifest. A project depends on another when its manifest names it as a local dependency; dependencies on registries or other repositories are ignored. A changed file belongs to the nearest project above it. The radius is every project that depends on a changed one, directly or through others.

Ecosystem Manifest Local dependencies read
Rust Cargo.toml path dependencies, workspace = true resolved through [workspace.dependencies], in [dependencies], [dev-dependencies], [build-dependencies] and their [target.*] forms
JavaScript / TypeScript package.json any dependency whose name is another package of the repository (npm, yarn and pnpm workspaces), plus file: and link:
Elixir mix.exs path: dependencies and in_umbrella: true
Go go.mod, go.work required modules that are another module of the repository, and replace with a directory
Python pyproject.toml any requirement whose name is another project of the repository (whatever the case, and whichever of -, _, .), and those given a path in [tool.uv.sources] or in the tables of Poetry; read from [project] (dependencies, optional-dependencies), [dependency-groups], [build-system] requires, [tool.poetry] and the development groups of uv and PDM
Blast radius — projects reached through their manifests
──────────────────────────────────────────────────────────────────────────────
 3 of 6 projects reached (50%), 2 direct
 Changed: libs/core

 Changed    Reaches         Distance  Scope  Via
 libs/core  apps/inventory         1
 libs/core  libs/locker            1
 libs/core  apps/parcels           2         libs/locker
──────────────────────────────────────────────────────────────────────────────
Changed files outside every project (reach unknown): Makefile
  • Scope: a dev dependency (dev or test only) reaches the dependent, whose tests use the changed project, and stops there: the changed project is not part of what the dependent ships, so the dependents of the dependent are not reached. build and optional dependencies carry on like runtime ones.

  • Workspace roots: a Cargo.toml with [workspace], a package.json with workspaces (or next to a pnpm-workspace.yaml), an umbrella mix.exs with apps_path, a go.work, a pyproject.toml with [tool.uv.workspace]. A change to the manifest or the lock file at such a root (Cargo.lock, package-lock.json, yarn.lock, pnpm-lock.yaml, bun.lock, mix.lock, uv.lock) reaches every project under it at distance 1, with scope workspace, and carries on from them. A workspace root is a project itself only when it declares one ([package] in Cargo, app: in mix, [project] in Python); a package.json at a workspace root never is.

  • Inert files reach nothing: a change to documentation (.md, .mdx, .rst, .adoc, .txt) breaks no build and no test. It does not count as a change to its project, nor as a file of unknown reach. .kimun.toml can declare more:

    [impact]
    inert = ["scripts/**", "notebooks/**"]   # globs, relative to the repository
    
  • Files outside every project (CI workflows, shared configuration) are listed apart. Their reach is unknown, not zero.

  • --affected prints the projects whose builds and tests the diff calls for, one per line, and nothing else: the changed and the reached ones. If any changed file is outside every project, it prints all projects and says why on stderr — skipping a test suite is worse than running one too many. It reads only the diff and the manifests, not the history.

  • A repository with a single project gets a line saying this level does not apply, rather than "0 reached".

  • node_modules, vendor and testdata are never searched for manifests, nor are deps, _build and target (unless they sit under src, lib or app, where they are part of the project), nor is a fixtures directory inside a test directory. An end-to-end suite with its own manifest (test/e2e/package.json) is a project.

Limits:

  • mix.exs is code and is read as text. A dependency whose path is built at run time (Path.expand(...), string interpolation, a generated list) cannot be attributed; the report names the manifest and how many it missed.
  • Of Python only pyproject.toml is read. A project declared in setup.py (which is code) or setup.cfg is not seen, nor is a local dependency written in requirements.txt (-e ../lib). A pyproject.toml that only configures tools, with neither [project] nor [tool.poetry], is not a project. Extras (optional-dependencies) are optional; dependency groups are dev.
  • Coupling across ecosystems is not visible: a web client and the service whose API it calls have no manifest dependency between them.
  • A project nested in another (assets/package.json inside a Phoenix application) has no dependency to or from the one that contains it unless a manifest declares one.
  • The graph is read from the working tree. The files of a project the diff deletes or moves away belong to no project any more: their reach is unknown, and the manifests still naming it are reported as not read.

Blast radius: source files

Inside the projects the change affects: which source files use what changed, and which of them no test exercises. This is the question "the tests of the module I changed pass; who else calls it?".

The first line is the answer in short: how many files call what changed, and how many of them have no test. Radius is the count of files that call what changed, and of those that use them. Upper bound is what it would be without knowing which functions changed.

Structural radius — source files that use what changed
──────────────────────────────────────────────────────────────────────────────
 1 file calls what changed, 1 of them with no test
 Changed: lib/booking/insights.ex
 Functions: arrange
 Radius: 1 of 6 source files (17%): 1 at distance 1
 Not in the radius: 1 that refer to the module without calling it
 Upper bound, whatever the function: 4 files (67%)

 Tests  Dependent
  none  lib/booking_web/controllers/insight_controller.ex
            calls Insights.arrange
  none  lib/booking/export.ex
            refers to the module without calling it
──────────────────────────────────────────────────────────────────────────────
No test reaches 1 of the files that call what changed; an integration test is probably missing:
  lib/booking_web/controllers/insight_controller.ex
No test in the change exercises a file that uses what changed.
1 more with no test use the module without a call that tells whether the change concerns them.

How it is measured:

  • The dependency graph of km deps is read backwards from the changed source files.

  • In Elixir the change is narrowed to functions: the lines the diff touches tell which functions changed, and a change to a private function is carried to the public ones that reach it through local calls. A file that uses the module is then one of three: it calls a function that changed, it refers to the module without calling it (a struct, an import, a use), or it only calls functions the change leaves alone, and is not listed. Each changed file is narrowed on its own. Outside the functions, a touched alias or require changes none (it only names what the touched functions use), and a touched module attribute changes the functions that read it. A use, an import, a defstruct, or an attribute no function reads may concern every function: that file is not narrowed, every use of it counts, and the report says which line it was. A new file is never narrowed.

  • In Python the change is narrowed to the top-level names of the module: its functions, classes and assignments. A touched method changes its class; a decorator belongs to what it decorates; a name that uses a changed one changes too, private or not, since nothing keeps another file from importing it. A file that uses the module calls what changed when it takes one of those names: from m import name, m.name on a module it imports (under its alias too), or, after from m import *, a name it goes on to mention. A module handed over as a value may give any of its names. One imported with nothing read on it only refers to the module. Imports, the docstring, an if or a try that only chooses imports, and the if __name__ == "__main__": block change no name. Any other code at the left margin runs when the module is imported and may concern every name: the file is not narrowed. Not seen: names reached at run time (getattr, a registry filled by decorators, mock.patch("m.name")), and which callers use the method that changed. A name a package re-exports is followed through its __init__.py, one distance further.

  • The radius starts at the files that call what changed and follows who uses them, file by file. A file that only refers to the module, without a call that tells, is listed but does not carry the radius on: a schema is named by half a project, and following all of that says nothing. Files that only pass through a dependent the change leaves alone are not counted either. Past the first step the radius is still by file, not by function, so it stays an estimate from above. The upper bound is what the radius would be if every use of a changed file counted, whatever the function: in a codebase where everything goes through a few contexts it is most of the project, which is why the radius is the number to read.

  • Tests says how the dependent is protected. A test rarely names everything it exercises — a controller or a live view is tested through its route, a helper through the views that use it — so protection comes in degrees:

    Tests Protection When
    a number direct That many test files refer to it, request a route it serves, or sit at the same place in the source and test layout (lib/a/b.ex and test/a/b_test.exs)
    named named A test carries its name a directory apart (live/page_live.ex and page_live_test.exs), or the name of the directory it is in (page_live/index.ex and page_live_test.exs). A test at the place of a source file is the test of that file and names no other: app_test.exs beside app.ex says nothing of the files in app/
    users users It has no test of its own, but a file that uses it has one
    none none No test reaches it

    Test support (test/support/), configuration and scripts are not tests: a factory refers to everything and would make everything look protected.

  • A file that calls what changed and that no test reaches is unprotected: the change can break it without any test noticing. That is the warning. Dependents are listed from the least protected.

  • Entry points are told apart. A command-line task or a script is run, not used: no test of something else passes through it, and few have one of their own. With no test they get a line of their own instead of the warning. They are the files under mix/tasks/, management/commands/, bin/ and scripts/ that no source file uses, plus what .kimun.toml declares:

    [impact]
    entry_points = ["**/endpoint.ex"]   # globs, relative to the repository
    
  • In Elixir, a test that requests a path protects the module that serves it. The routes are read from the Phoenix router of the project of the test, with the path and the alias of every scope around them; :id matches any one segment, and a segment the test writes at run time (#{order.id}) matches only a parameter of the route: a request for one order does not protect /orders/new.

  • In Elixir, what a framework relates by convention counts as a use. A Phoenix controller uses the views named after it (PageController and PageJSON, PageHTML, PageView), so the test of the controller protects them. A module uses the components its templates render, whether written in it as ~H or kept in a .html.heex file beside it (page/index.ex and page/index.html.heex) or in a directory named after it (page_html.ex and page_html/home.html.heex).

It is measured for the languages whose graph reflects usage: Elixir, JavaScript/TypeScript, Kaikai, Python and Rust. For Go the block says it is not available rather than report a radius drawn on declarations. Only the projects the change affects are read; the whole repository when the reach over projects is unknown.

Limits: a test at the same place, or named after a file, may not exercise the call that changed, and one that refers to a file may mock what it calls — the column says a test exists, not that it covers. users is weaker still: it says something that uses the file is tested. Function names are compared without arity. Modules named at run time (apply/3, configuration) or generated by macros are not seen. A request is read when its path is written in the call (live(conn, ~p"/orders")), not when it comes from a variable or a helper, and a route when it is declared on one line.

Diffusion

How spread the change is. Kamei et al. found diffusion among the strongest predictors of a defect-inducing change.

Measure Meaning
Files changed Files added, modified, renamed or deleted
Directories Distinct directories holding a changed file
Subsystems Distinct top-level directories (files at the root form one more)
Lines added / deleted Binary files count no lines
Entropy Shannon entropy of the modified lines over the files, divided by its maximum: 0 when one file holds every modified line, 1 when all the files hold the same amount

Logical radius

Files that usually change with the files of the diff and are not in it — a change that may have been forgotten. It catches coupling the code does not declare: tests, configuration, migrations.

Confidence = shared_commits / commits of the changed file

A file is reported when some changed file reaches --min-confidence with at least --min-shared shared commits. Confidence is directional, unlike the strength of km tc: a file that changed three times, always with one that changed a hundred times, has strength 1.0 but is needed in 3% of the changes to the other.

  • History ends at the merge base: the commits of the diff are never evidence for themselves.
  • Commits touching more than --max-changeset files are ignored, and the report says how many: a reformat or a rename across the project relates its files to each other by accident.
  • A changed file with no history (new, or outside --since) predicts nothing. It is listed apart, so its silence is not read as "no impact".
  • Files that no longer exist are not reported.
  • Test files are always part of the analysis: a test that usually changes with the code is a change worth expecting.

Options:

Flag Description
--since-ref REF Git ref to diff against, e.g. origin/main, HEAD. Required unless --diff or --pr is given
--until-ref REF Measure up to this ref instead of the working tree (needs --since-ref)
--diff FILE Measure a patch in git format; - reads stdin
--pr NUMBER Measure a GitHub pull request; requires gh installed and authenticated
--since DURATION Only consider history since this time (e.g. 6m, 1y, 30d)
--min-confidence F Minimum confidence to report a missing file (default: 0.5)
--min-shared N Minimum shared commits to report a missing file (default: 3)
--max-changeset N Ignore commits touching more than N files as evidence (default: 30)
--affected Print only the changed and reached projects, one per line
--top N Show only the top N missing files (default: 20)
--format {table,json,short,terse} Output format (default: table)

Example output:

Change Impact — diff against main

Blast radius — projects reached through their manifests
──────────────────────────────────────────────────────────────────────────────
 Single project (.): no other project to reach; this level does not apply.
──────────────────────────────────────────────────────────────────────────────

Diffusion
  Files changed           5
  Directories             3
  Subsystems              2
  Lines added           120
  Lines deleted          30
  Entropy              0.82  (0 = one file holds the change, 1 = evenly spread)

Logical radius — files that usually change with this diff and are not in it
──────────────────────────────────────────────────────────────────────────────
 Missing file      Confidence   Shared  Changes with
──────────────────────────────────────────────────────────────────────────────
 src/tc/report.rs        0.80     8/10  src/tc/mod.rs (+1 more)
 README.md               0.50     6/12  src/cli.rs
──────────────────────────────────────────────────────────────────────────────
No history before the diff (new or never committed): src/impact/mod.rs
Generated files ignored: 1

When the rows are too wide for a table (long paths), each missing file is listed on a line of its own with its evidence below.

JSON output, for tools and LLMs

--format json carries everything the table shows, and the lists the table cuts short. An agent reviewing a change can read it in this order:

km impact --since-ref origin/main --format json
Field Meaning
source The change measured: diff against main, PR #12, patch from stdin
structural.functions Functions the change affects (public ones in Elixir, top-level names in Python), over the files that tell them; null when none could be narrowed
structural.narrowing[] Per changed file: functions, or null with the reason every use of it counts
structural.direct[] Every file that uses a changed file: file, exposure (calls, refers, elsewhere), protection (direct, named, users, none), calls, tests, tests_in_diff, entry_point
structural.unprotected[] Files that call what changed and that no test reaches, not even through what uses them — where an integration test is missing
structural.untested_entry_points[] Command-line tasks and scripts that call what changed and have no test; not counted as unprotected
structural.unknown_without_tests[] Files that use the changed module without a call that tells, and have no test
structural.change_tests_a_dependent Whether a test in the change protects a file that uses what changed
structural.radius files, source_files and share (0 to 1): the radius as a number
structural.reach[] The files of the radius, by distance
structural.upper_bound Files reached if every use of a changed file counted, whatever the function
structural.unavailable[] Languages of changed files the source level is not measured for
projects.changed[], projects.reached[] Projects holding a changed file, and those reached, each with origin, distance, via, scope
projects.affected[] Projects whose builds and tests the change calls for (what --affected prints)
projects.outside[] Changed files that belong to no project: their reach is unknown
projects.inert[] Changed files that reach nothing: documentation, and what .kimun.toml declares inert
diffusion Files, directories, subsystems, lines and entropy of the change
logical_radius.missing[] Files that usually change with the change and are not in it, with every trigger

km ai exposes the command to an LLM as the tool km_impact, and the skill installed by km ai skill documents it.

Shared reads as shared commits over the commits of the changed file. (+1 more) means another changed file predicts the same missing file; --format json lists every one. --format terse prints the number of missing files.

Note: File renames are not tracked across git history. A file renamed in the diff itself keeps the history of its old path.

km churn -- Code churn analysis

Measures pure change frequency per file from git history (commit count only, no complexity weight). Identifies the most frequently modified files — high churn without a corresponding quality improvement is a maintenance signal.

km churn [path]

Options:

Flag Description
--top N Show only the top N files (default: 20)
--sort-by METRIC Sort by commits (default), rate (commits/month), or file
--since DURATION Only consider commits since this time (e.g. 6m, 1y, 30d)
--format {table,json,short,terse} Output format (default: table)

Example output:

Code Churn — Change Frequency
──────────────────────────────────────────────────────────────────────────────
 File                     Language  Commits   Rate/mo   First Seen   Last Seen
──────────────────────────────────────────────────────────────────────────────
 src/main.rs                  Rust       18      3.2    2025-01-10  2026-03-28
 src/loc/counter.rs           Rust        7      1.3    2025-01-10  2026-02-14
 src/dups/detector.rs         Rust        7      1.2    2025-02-01  2026-02-20
──────────────────────────────────────────────────────────────────────────────

km smells -- Code smell detection

Detects common code quality issues per file using text-based heuristics (no AST required). Only languages with complexity marker support are analyzed (same set as km cycom: Rust, Python, JS/TS, C/C++, Go, etc.).

km smells [path]

Smell types

Smell Description
long_function Function body exceeds --max-lines (default: 50)
long_params Function has more than --max-params parameters (default: 4)
todo_debt TODO, FIXME, HACK, XXX, or BUG in comment lines
magic_number Bare numeric literals in code (excluding 0, 1, 2, -1 and const/let declarations)
commented_code Two or more consecutive comment lines containing code-like patterns

Options:

Flag Description
--top N Show only the top N files by smell count (default: 20)
--max-lines N Maximum function body lines before flagging (default: 50)
--max-params N Maximum parameter count before flagging (default: 4)
--files FILE Analyze only these specific files (repeatable). Useful for scripting
--since-ref REF Analyze only files changed since this git ref (e.g. origin/main, HEAD~1). Ideal for CI
--format {table,json,short,terse,github,codeclimate} Output format (default: table). github emits GitHub Actions annotations; codeclimate (alias: gitlab) emits CodeClimate JSON for GitLab Code Quality

The table breaks each file's smell count down by type, with one column per smell kind (magic, long, param, todo, comm) and a per-column total in the footer.

Example output:

Code Smells
──────────────────────────────────────────────────────────────────────
 File                            Total  magic  long  param  todo  comm
──────────────────────────────────────────────────────────────────────
 src/loc/counter.rs                 12      7     1      0     4     0
 src/main.rs                         6      2     0      0     4     0
 src/dups/detector.rs                3      0     2      1     0     0
──────────────────────────────────────────────────────────────────────
 Total (3 files)                    21      9     3      1     8     0

km deps -- Dependency graph analysis

Analyzes internal module dependencies by parsing import/use/require statements. Builds a directed graph of file-level coupling and detects cycles using Tarjan's SCC algorithm.

km deps [path]

Supports Elixir (every module referred to in the code, with alias undone; see the notes below), Rust (every path that names a module of the workspace: use, crate::, super::, a child module; see the notes below), Python (import and from … import, absolute and relative; see the notes below), JavaScript/TypeScript (relative import/require), Go (imports matching the module path from go.mod), and Kaikai (import a.b.c, including the as and .{…} forms). External dependencies (crates, npm packages, the Kaikai stdlib) are ignored.

Files in any other language are left out of the graph instead of being listed with zero dependencies. The table footer, the unsupported array of the JSON output and the unsupported:N field of the short format say how many files were skipped, so "not measured" is never shown as "no dependencies".

Elixir notes:

  • Dependencies are between modules, and most need no import, so every module name in the code counts as a reference: calls, structs, use, import, require, @behaviour, defimpl. Comments, strings, heredocs and sigils are set aside first, so a doctest is not a dependency.
  • alias is undone, including as:, grouped and multi-line forms, and __MODULE__. The statement itself is not a use.
  • Nested defmodules are named after the module that contains them, told by indentation as mix format leaves it.
  • A module defined in several files (projects made from one template) resolves to the file nearest the one referring to it.
  • Comments and literals hold no references, but the code a string interpolates does: "Total: #{Orders.total(order)}" uses Orders.
  • A Phoenix controller uses the views named after it (PageController and PageJSON, PageHTML, PageView), and a module uses the components its ~H templates render.
  • Not seen: modules named at run time (apply/3, configuration), those generated by macros, and those a Phoenix router names under the alias of a scope.

Rust notes:

  • A dependency is a path: use crate::git::GitRepo, a qualified super::analyzer::run(x), a call on a child module (report::print(x)). Groups, as, self, globs and multi-line use are read. mod x; only says where a module lives and adds no edge.
  • Each crate is a tree of modules grown from its root (src/lib.rs, src/main.rs, a file of src/bin, tests, examples or benches, build.rs) by its mod declarations, #[path] included. A path leads to the file of the deepest module it names: the item may be defined there or only re-exported.
  • Other targets of a package reach its library by name (my_app::orders from tests/ or main.rs), and so do the other crates of the workspace. The name comes from [package] name, with - read as _.
  • A type uses the files that hold its impl blocks, since what they define is reached through the type.
  • For km impact, a file that holds #[test] functions has a test of its own; a file of tests/ that holds them, or a tests.rs module, is a test. What a package runs (src/main.rs, src/bin, examples, benches, build.rs) is an entry point.
  • Comments, strings and $crate in a macro name nothing.
  • Not seen: what a macro generates or names, include!, a library with a [lib] path or name of its own, a dependency renamed in Cargo.toml, and modules behind cfg, which all count. A use only from an inline test module still makes the file a dependent. A test that runs the binary (assert_cmd, CARGO_BIN_EXE_*) names no file, so it protects none. Two packages of the same name in one repository are not told apart.

Python notes:

  • Every import a.b and from a.b import c is read, wherever it is written: in a function, under if TYPE_CHECKING:, over several lines in parentheses or with a backslash. One written in a docstring or a comment is not an import.
  • A dotted path names a/b.py or the package a/b/__init__.py; a stub (.pyi) stands for a module with no source. Only the deepest module is used: import a.b.c adds no edge to a/__init__.py.
  • In from a.b import c, c is the submodule a/b/c.py when that file exists, and a name a.b defines otherwise.
  • A relative import starts at the package of the importing file, one level up per extra dot.
  • An absolute import is looked up from each directory above the importing file that is not itself a package (it holds no __init__.py), nearest first, and from the src directory under each. That covers a project run from its root, a src layout with tests/ beside it, and several projects in one repository. Then come the roots the nearest pyproject.toml above declares: where the build backend finds the packages (where and package-dir of setuptools, packages of Poetry, sources and packages of Hatch, python-source of maturin, package-dir of PDM, module-root of uv) and what pytest adds (pythonpath). What is found under none of them is external: the standard library, installed packages.
  • For km impact, test_*.py, *_test.py and tests.py are tests, and conftest.py is test support, which protects nothing; __main__.py, setup.py and manage.py are entry points, and so is what sits under management/commands.
  • Not seen: modules named at run time (importlib, __import__, Django settings and INSTALLED_APPS), roots added at run time (sys.path, PYTHONPATH, a .pth file) or declared in setup.py, setup.cfg or pytest.ini, and a namespace package spread over several roots. A name a package re-exports leads to its __init__.py, and from there to the module that defines it.

Kaikai notes:

  • import a.b.c names a/b/c.kai relative to a package root, not to the importing file. Each ancestor directory of the importing file is tried, nearest first, so run km deps on a directory that contains the package root.
  • When no such file exists, import a can name a package directory a/ that carries a kai.toml; the import then depends on every .kai file directly inside it.
  • An import that resolves to no analysed file is external and adds no edge.
  • The files of one Kaikai package merge, so a module can use a name declared in another file of its package without importing it. The import graph is therefore a lower bound on the real dependencies.
Flag Description
--format {table,json,short,terse} Output format (default: table)
--cycles-only Show only files that participate in a dependency cycle
--sort-by METRIC Sort by fan-out (default) or fan-in
--top N Show only top N files (default: 20)

Example output:

Dependency Graph
────────────────────────────────────────────────────────────────────────
 File                 Language Fan-In Fan-Out Cycle
────────────────────────────────────────────────────────────────────────
 report_helpers.rs        Rust     26       1    no
 util.rs                  Rust     25       2   yes
 walk.rs                  Rust     24       1    no
────────────────────────────────────────────────────────────────────────

Dependency cycles: 14
  Cycle 1 (3 files):
    cogcom/analyzer.rs
    cogcom/detection.rs
    cogcom/report.rs

km authors -- Per-author ownership summary

Summarizes code ownership across the project by author. Aggregates git blame data to answer "who knows what?" at the team level — complementing km knowledge (per-file view) with a team-level view.

km authors [path]

Options:

Flag Description
--since DURATION Only consider activity since this time (e.g. 6m, 1y, 30d)
--format {table,json,short,terse} Output format (default: table)

Example output:

──────────────────────────────────────────────────────────────────────
 Author              Owned      Lines  Languages    Last Active
──────────────────────────────────────────────────────────────────────
 E. Diaz                38       8432  Rust, TOML   2026-03-15
 R. Ramirez              4        312  Rust         2026-02-10
──────────────────────────────────────────────────────────────────────

km age -- File age analysis

Classifies source files as Active, Stale, or Frozen based on how long ago they were last modified in git history. Helps identify neglected or abandoned code.

km age [path]

Status classification

Status Condition Meaning
ACTIVE Modified within --active-days days (default: 90) Regularly touched
STALE Between --active-days and --frozen-days (default: 365) Neglected
FROZEN Not modified for more than --frozen-days days Potentially abandoned

Options:

Flag Description
--active-days N Days threshold for Active status (default: 90)
--frozen-days N Days threshold for Frozen status (default: 365)
--sort-by METRIC Sort by date (oldest first, default), status, or file
--status FILTER Show only files with this status: active, stale, or frozen
--format {table,json,short,terse} Output format (default: table)

Example output:

──────────────────────────────────────────────────────────────────────────────
 File                    Language     Last Modified  Days  Status
──────────────────────────────────────────────────────────────────────────────
 src/legacy/parser.rs    Rust           2023-01-15   840  FROZEN
 src/util.rs             Rust           2024-09-20   197  STALE
 src/main.rs             Rust           2026-03-01    34  ACTIVE
──────────────────────────────────────────────────────────────────────────────

  ACTIVE     12  (modified < 90 days)
  STALE       8  (90 days – 365 days)
  FROZEN      3  (not modified > 365 days)

km score -- Code health score

Computes an overall code health score for the project, grading it from A++ (exceptional) to F-- (severe issues). Uses only static metrics (no git required).

Breaking change in v0.14: The default scoring model changed from MI + Cyclomatic Complexity (6 dimensions) to Cognitive Complexity (5 dimensions). Use --model legacy to restore v0.13 behavior.

Non-code files (Markdown, TOML, JSON, etc.) are automatically excluded. Inline test blocks (#[cfg(test)]) are excluded from duplication analysis: the item under the attribute and nothing else, so the code after a test module is measured.

km score [path]
km score --model legacy [path]    # v0.13 scoring model

Dimensions and weights (default: cogcom)

Dimension Weight What it measures
Cognitive Complexity 30% SonarSource method, penalizes nesting
Duplication 20% Project-wide duplicate code %
Indentation Complexity 15% Stddev of indentation depth
Halstead Effort 20% Mental effort per LOC
File Size 15% Optimal range 50-300 LOC

Dimensions and weights (--model legacy)

Dimension Weight What it measures
Maintainability Index 30% Verifysoft MI, normalized to 0-100
Cyclomatic Complexity 20% Max complexity per file
Duplication 15% Project-wide duplicate code %
Indentation Complexity 15% Stddev of indentation depth
Halstead Effort 15% Mental effort per LOC
File Size 5% Optimal range 50-300 LOC

Each dimension is aggregated as a LOC-weighted mean across all files (except Duplication which is a single project-level value). The project score is the weighted sum of all dimension scores.

Grade scale

Grade Score range Grade Score range
A++ 97-100 C+ 73-76
A+ 93-96 C 70-72
A 90-92 C- 67-69
A- 87-89 D+ 63-66
B+ 83-86 D 60-62
B 80-82 D- 57-59
B- 77-79 F 50-56
F- 40-49
F-- 0-39

Options:

Flag Description
--model MODEL Scoring model: cogcom (default, v0.14+) or legacy (MI + cyclomatic, v0.13)
--trend [REF] Compare current score against a git ref (default: HEAD). Shows change: B- → B (+2.3). Useful for PR review: --trend origin/main
--fail-if-worse With --trend: exit with code 1 if the score dropped by more than --gate-tolerance
--gate-tolerance POINTS Score drop --fail-if-worse allows before failing (default: 0.01 with --gate-scope project, 0.5 with --gate-scope changed). Compares unrounded scores
--gate-scope {project,changed} What --fail-if-worse compares (default: project, the aggregate score). changed looks only at the files the diff touches: it fails if a modified or renamed file ends below the project score at the ref after dropping more than --gate-tolerance, or if the project's duplicated lines grow. Files above the project score, new files and deleted files never fail it, so removing healthy code cannot lower the verdict. The report lists every changed file with its before/after score
--fail-below GRADE With --trend: exit with code 1 if the score is below GRADE (e.g. B-). Overridable via .kimun.toml
--format {table,json,short,terse} Output format (default: table)
--include-tests Include test files in analysis (excluded by default)
--bottom N Number of worst files to show in "needs attention" (default: 10)
--min-lines N Minimum lines for a duplicate block (default: 6)

Example output:

Code Health Score
──────────────────────────────────────────────────────────────────
 Project Score:  B+ (84.3)
 Files Analyzed: 42
 Total LOC:      8,432
──────────────────────────────────────────────────────────────────
 Dimension                 Weight   Score   Grade
──────────────────────────────────────────────────────────────────
 Cognitive Complexity         30%    85.6   B+
 Duplication                  20%    91.3   A
 Indentation Complexity       15%    79.8   B-
 Halstead Effort              20%    85.1   B+
 File Size                    15%    89.2   A-
──────────────────────────────────────────────────────────────────

 Files Needing Attention (worst scores)
──────────────────────────────────────────────────────────────────
 Score  Grade  File                       Issues
──────────────────────────────────────────────────────────────────
  54.2  F      src/legacy/parser.rs       Cognitive: 42, Indent: 3.2
  63.7  D+     src/utils/helpers.rs       Effort: 15200, Indent: 2.4
  68.9  C-     src/core/engine.rs         Size: 1243 LOC
──────────────────────────────────────────────────────────────────

km score diff — Compare score against a git ref

Extracts the file tree at the given ref, computes the score for both snapshots, and shows a delta table per dimension. Useful for reviewing how commits impact code quality.

km score diff                          # compare vs HEAD (uncommitted changes)
km score diff --git-ref HEAD~1         # compare vs previous commit
km score diff --git-ref main           # compare vs main branch
km score diff --format json            # machine-readable output

Options:

Flag Description
--git-ref REF Git ref to compare against (default: HEAD)
--model MODEL Scoring model: cogcom (default) or legacy
--format {table,json,short,terse} Output format (default: table)
--bottom N Number of worst files to show (default: 10)
--min-lines N Minimum lines for a duplicate block (default: 6)

km report -- Comprehensive metrics report

Generates a multi-section report combining all static code metrics in a single pass: lines of code, duplicates, indentation, Halstead, cyclomatic complexity, cognitive complexity, and maintainability index.

km report [path]

Options:

Flag Description
--top N Show only the top N files per section (default: 20)
--min-lines N Minimum lines for a duplicate block (default: 6)
--full Show all files instead of truncating to top N
--format {table,json,short,terse} Output format (default: table)

Project configuration (.kimun.toml)

Run km init to analyze your project and generate a calibrated .kimun.toml in one step:

$ km init
Analyzing project... done.

Current state:
  avg function length: 38 lines  →  suggested max_lines = 45
  avg param count:     3.2       →  suggested max_params = 4
  dup ratio:           4.1%      →  suggested max_dup_ratio = 5.0
  health score:        B+        →  suggested fail_below = B

Write .kimun.toml with these values? [Y/n]

Use --yes to skip the prompt. Add -y in CI to write the file non-interactively.

Alternatively, place a .kimun.toml file manually in the root of your repository to set project-level defaults for thresholds and quality gates. km searches for the file at the git repository root, falling back to the current directory.

CLI flags always take precedence over .kimun.toml, which in turn takes precedence over built-in defaults.

[smells]
max_lines  = 30    # flag functions longer than N body lines (default: 50)
max_params = 3     # flag functions with more than N parameters (default: 4)

[dups]
min_lines      = 8     # minimum block size for duplication detection (default: 6)
                       # also applies to `km report` and `km score`
max_duplicates = 10    # CI gate: fail if duplicate groups exceed N
max_dup_ratio  = 5.0   # CI gate: fail if duplicated-lines ratio exceeds this %

[score]
model      = "cogcom"  # scoring model: cogcom (default) or legacy
fail_below = "B-"      # CI gate: fail if health score is below this grade

[age]
active_days = 60    # files modified within N days are Active (default: 90)
frozen_days = 180   # files not modified for more than N days are Frozen (default: 365)

[tc]
min_degree   = 5    # minimum commits per file to include in coupling analysis (default: 3)
min_strength = 0.5  # only show pairs with coupling strength >= this value

[hotspots]
complexity = "cogcom"  # complexity metric: indent (default), cycom, or cogcom

[impact]
inert = ["scripts/**"]  # changed files that reach nothing, besides documentation
entry_points = ["**/endpoint.ex"]  # files run rather than used, besides tasks and scripts

All sections and fields are optional — omit any you don't need. A fully documented template is available at .kimun.toml.example.

Features

  • Respects .gitignore rules automatically
  • Deduplicates files by content hash (identical files counted once)
  • Detects languages by file extension, filename, or shebang line
  • Supports nested block comments (Rust, Haskell, OCaml, etc.)
  • Handles pragmas (e.g., Haskell {-# LANGUAGE ... #-}) as code
  • Mixed lines (code + comment) are counted as code, matching cloc behavior

Supported Languages

Language Extensions / Filenames
Bourne Again Shell .bash
Bourne Shell .sh
C .c, .h
C# .cs
C++ .cpp, .cxx, .cc, .hpp, .hxx
Clojure .clj, .cljs, .cljc, .edn
CSS .css
Dart .dart
Dockerfile Dockerfile
DOS Batch .bat, .cmd
Elixir .ex
Elixir Script .exs
Erlang .erl, .hrl
F# .fs, .fsi, .fsx
Go .go
Gradle .gradle
Groovy .groovy
Haskell .hs
HTML .html, .htm
Java .java
JavaScript .js, .mjs, .cjs
JSON .json
Julia .jl
Kaikai .kai
Kotlin .kt, .kts
Lua .lua
Makefile .mk, Makefile, makefile, GNUmakefile
Markdown .md, .markdown
Nim .nim
Objective-C .m, .mm
OCaml .ml, .mli
Perl .pl, .pm
PHP .php
Properties .properties
Python .py, .pyi
R .r, .R
Ruby .rb, Rakefile, Gemfile
Rust .rs
Scala .scala, .sc, .sbt
SQL .sql
Swift .swift
Terraform .tf
Text .txt
TOML .toml
TypeScript .ts, .mts, .cts
XML .xml, .xsl, .xslt, .svg, .fsproj, .csproj, .vbproj, .vcxproj, .sln, .plist, .xaml
YAML .yaml, .yml
Zig .zig
Zsh .zsh

Language-specific notes

  • Kaikai — #[...] opens an attribute, not a # comment, so attributes count as code. Documentation attributes (#[doc("...")], including the multi-line #[doc("""...""")] form) count as comments and are excluded from the complexity, Halstead, and smell analyses.
  • Interior lines of multi-line strings (Kaikai and Python triple-quoted literals) count as code for km loc, but are excluded from cyclomatic, cognitive, Halstead, and smell analyses: prose and embedded data are not control flow.

Development

cargo build              # build debug binary
cargo test               # run all tests
cargo clippy             # lint (zero warnings required)
cargo tarpaulin --out stdout  # coverage report

References

The metrics and methodologies implemented in Kimün are based on the following sources:

Books

  • Adam Thornhill, Your Code as a Crime Scene (Pragmatic Bookshelf, 2015). Basis for hotspot analysis (ch. 4–5), temporal coupling (ch. 7), knowledge maps / code ownership (ch. 8–9), and indentation-based complexity as a proxy for code quality.
  • Adam Thornhill, Software Design X-Rays (Pragmatic Bookshelf, 2018). Extends the crime scene metaphor with additional behavioral code analysis techniques.

Papers and standards

  • Maurice H. Halstead, Elements of Software Science (Elsevier, 1977). Defines the operator/operand metrics: vocabulary, volume, difficulty, effort, estimated bugs, and development time.
  • Thomas J. McCabe, "A Complexity Measure", IEEE Transactions on Software Engineering, SE-2(4), December 1976, pp. 308–320. Introduces cyclomatic complexity as a measure of independent paths through a program's control flow graph.
  • Paul Oman & Jack Hagemeister, "Metrics for Assessing a Software System's Maintainability", Proceedings of the International Conference on Software Maintenance (ICSM), 1992. Original Maintainability Index formula combining Halstead Volume, cyclomatic complexity, and lines of code.
  • Microsoft, Code Metrics — Maintainability Index range and meaning. Visual Studio variant: normalized to 0–100 scale, no comment-weight term.
  • Verifysoft, Maintainability Index. Extended MI formula with a comment-weight component (MIcw) that rewards well-commented code.
  • Yasutaka Kamei et al., "A Large-Scale Empirical Study of Just-in-Time Quality Assurance" (IEEE TSE 39(6), 2013). Basis for the diffusion measures of km impact.
  • Thomas Zimmermann, Andreas Zeller, Peter Weissgerber, Stephan Diehl, "Mining Version Histories to Guide Software Changes" (IEEE TSE 31(6), 2005). Basis for the logical radius of km impact.

License

See Cargo.toml for package details.