pkgrank

Ranks nodes in a dependency graph by structural importance (PageRank, betweenness, degree).

Two axes of analysis:

• File-level (files): which source files are structural hotspots, forming cycles, or high churn risk? Polyglot (Rust, Python, JS/TS, Go), works on any local path or GitHub URL.
• Package-level (analyze): which packages in a dependency tree are most central, most depended-on, most risky to change? Supports Cargo, npm, Python, and Go.

Install

cargo install pkgrank
pkgrank --help

Quick start

# File-level: structural hotspots in any project (no toolchain needed)
pkgrank files .
pkgrank files tokio-rs/tokio
pkgrank files https://github.com/fastapi/fastapi

# File-level with git churn risk overlay
pkgrank files . --git

# Focus on a specific file
pkgrank files . --focus main.rs

# Directory-level aggregation for large codebases
pkgrank files astral-sh/ruff --directory

# CI gate: fail on architectural violations
pkgrank files . --fail-on-violation

# What files are affected by a change?
pkgrank files . --affected src/parser.rs

# Package-level: rank dependencies by importance (auto-detects ecosystem)
pkgrank analyze
pkgrank analyze path/to/npm-project
pkgrank analyze path/to/python-project

# Blast radius: what breaks if serde changes?
pkgrank blast-radius serde
pkgrank blast-radius express path/to/npm-project

# Upgrade priority: which outdated deps matter most? (Cargo only)
pkgrank upgrade-priority

File-level analysis (pkgrank files)

Analyze the import graph within a project. Static parsing (no toolchain required). Works across Rust, Python, JS/TS, and Go.

# Any local project (ecosystem auto-detected)
pkgrank files .

# Any GitHub repo via URL or shorthand
pkgrank files tokio-rs/tokio
pkgrank files https://github.com/django/django

# Git churn risk: combine structural centrality with change frequency
pkgrank files . --git

# Focus on one file: see imports, dependents, co-changers, blast radius
pkgrank files . --git --focus lib.rs

# Directory aggregation for large codebases
pkgrank files astral-sh/ruff --directory

# Include test files (excluded by default)
pkgrank files . --include-tests

# Cache results for repeated queries
pkgrank files . --cache

# CI: fail if cycles or layer violations exist
pkgrank files . --fail-on-violation

# Affected files: what breaks if these files change?
pkgrank files . --affected src/graph.rs,src/index.rs

Output includes:

• Structural role: foundation (high in, low out), hub (high both), consumer (low in, high out), leaf
• Instability: I = out/(in+out), 0 = stable provider, 1 = unstable consumer
• Blast radius: transitive dependents (how many files break if this one changes)
• Cycle detection: Tarjan's SCC, files in cycles marked with *
• Orphan detection: files with no imports and no dependents
• Churn risk (--git): structural centrality * change frequency. Files marked !! are in the danger zone (central + volatile)
• Bus factor (--git): unique contributors per file
• Co-change coupling (--git): files that change together in commits
• Layer violations: detects when stable files import from unstable files (Clean Architecture dependency rule)
• External deps: which third-party packages each file imports

Cross-project queries via SQLite (auto-enabled):

pkgrank query hotspots          # highest churn risk files
pkgrank query deps              # most-used external deps
pkgrank query projects          # list all analyzed projects
pkgrank query "files lib.rs"    # search for files by name
pkgrank query compare           # diff between last two snapshots
pkgrank query drift             # centrality changes over time

For JS/TS projects, resolves tsconfig.json path aliases (@/, etc.) and npm workspace packages (@scope/pkg). Detects cross-language seams (PyO3, NAPI) between Rust and Python/JS.

Package-level analysis (pkgrank analyze)

Rank packages in a dependency graph by centrality. Auto-detects ecosystem from directory contents.

# Auto-detect: finds Cargo.toml, package-lock.json, uv.lock, or go.mod
pkgrank analyze

# Explicit ecosystem override
pkgrank analyze --ecosystem js path/to/project
pkgrank analyze --ecosystem python path/to/project
pkgrank analyze --ecosystem go path/to/project

# Choose metric
pkgrank analyze --metric consumers-pagerank -n 10

# JSON output
pkgrank analyze --format json --json-limit 200

Graph model: nodes are packages, directed edges are $A \to B$ iff package A depends on package B.

Interpretation:

• PageRank on the depends-on graph surfaces shared dependencies / substrate packages.
• Consumer PageRank (reversed graph) surfaces top-level orchestrators / consumers.

Blast radius

Show everything that transitively depends on a package:

pkgrank blast-radius serde
pkgrank blast-radius express path/to/npm-project
pkgrank blast-radius --workspace-only=false -n 20 serde

Output is sorted by BFS depth (closest dependents first), then by PageRank within each depth level.

Upgrade priority (Cargo only)

Combine cargo outdated with centrality ranking to prioritize which upgrades matter most:

pkgrank upgrade-priority -n 15

Requires cargo-outdated. Scores each outdated dep by 10*ln(dependents+1) + 1000*pagerank + urgency_bonus.

TLC score

The triage and view commands produce a TLC (Top-Level Cost) score for each crate and repo:

• Blast radius: 10 * ln(transitive_dependents + 1)
• Centrality: 1000 * pagerank
• Boundary complexity: number of third-party dependencies

Higher TLC = more structurally important and/or more exposed. It is a triage signal, not a quality metric.

Cargo workspace tools

These subcommands use cargo metadata and are specific to Rust/Cargo workspaces.

Module-level analysis (Rust only)

pkgrank modules shells out to cargo-modules and ranks items by coupling. This is intra-package analysis: which modules, types, or traits inside a single crate are the coupling hotspots?

cargo install cargo-modules
pkgrank modules --manifest-path ../Cargo.toml -p walk --lib -n 25
pkgrank modules-sweep --manifest-path ../Cargo.toml -p walk -p innr --lib

CLI defaults include types + traits (functions hidden). MCP defaults are more conservative; use preset like file-api or file-full for the CLI-like view.

JSON output shape (stable wrapper)

For commands that support --format json, the JSON is wrapped for forwards-compatible parsing:

{
  "schema_version": 1,
  "ok": true,
  "command": "analyze|modules|modules-sweep|cratesio",
  "rows": [ /* ... */ ]
}

Auto-JSON when piped

When stdout is not a TTY, output defaults to JSON. This makes pkgrank composable with jq without requiring --format json.

MCP stdio server

pkgrank mcp-stdio runs an MCP server over stdio for integration with Cursor and other editors.

Toolset selection:

• Default: slim (small tool surface)
• PKGRANK_MCP_TOOLSET=full: advanced tools (module/type graph, polyglot, files)
• PKGRANK_MCP_TOOLSET=debug: internal artifact-inspection tools

Configurable invariant rules

Cross-axis dependency rules are loaded from dev_repos_overview.json (under --root at evals/arch/dev_repos_overview.json). Add a forbidden_edges array:

{
  "axes": { "core": ["libfoo", "libbar"], "apps": ["myapp"] },
  "forbidden_edges": [
    { "from": "core", "to": "apps" }
  ]
}

Tests

• Default test suite is offline/deterministic, uses local targets.
• URL-backed tests (crates.io crawl) require PKGRANK_E2E_NETWORK=1.

Non-goals

• Security / advisory analysis: use cargo audit or cargo deny.
• Graph visualization: output is ranked tables and JSON. Use cargo-depgraph or Graphviz.
• Circular dependency breaking: cycles are detected but no suggestions for breaking them.
• License compliance: no license analysis.
• Build / test / deploy: pkgrank analyzes structure, not execution.

Dependencies

• Centrality algorithms delegated to graphops (PageRank / PPR / betweenness / reachability).