Dependency Auditing and License Compliance Checking: A Complete Guide to the Claude Skills Tool

The Claude Skills repository provides a self-contained, pure-Python tool that scans project dependencies, detects SPDX licenses, evaluates compatibility against a configurable matrix, and generates detailed compliance reports suitable for CI/CD enforcement.

Dependency auditing and license compliance checking ensures that third-party packages do not introduce legal conflicts or incompatible obligations into your codebase. The alirezarezvani/claude-skills repository ships a zero-dependency utility located at engineering/dependency-auditor/scripts/license_checker.py that performs deep license analysis using only Python’s standard library. This article explains the architecture, usage patterns, and integration strategies for automating license compliance in software projects.

How the LicenseChecker Class Orchestrates Analysis

The audit engine centers on the LicenseChecker class, which encapsulates the entire workflow from dependency discovery to report generation. During initialization, the constructor loads three critical data structures that remain extensible without modifying core logic.

Building the License Database and Compatibility Matrix

In __init__, the checker invokes _build_license_database(), _build_compatibility_matrix(), and _build_license_patterns() to prepare for analysis. The license database maps SPDX identifiers—such as MIT, Apache-2.0, GPL-2.0, and AGPL-3.0—to metadata including license type (permissive, copyleft, proprietary, or unknown), risk levels, and legal obligations. The compatibility matrix functions as a two-dimensional lookup table that determines whether a project’s license can legally incorporate a specific dependency license; for example, the matrix records that MIT is compatible with BSD-3-Clause but flags potential conflicts with GPL-2.0.

Pattern-Based License Detection

When package metadata lacks explicit SPDX declarations, the tool falls back to _detect_license_from_text(), which uses regex patterns built by _build_license_patterns(). These patterns recognize common license boilerplate inside plain-text LICENSE files, allowing the scanner to identify MIT or Apache-2.0 clauses even when developers omit standardized metadata.

Running Dependency Audits

The tool supports two primary workflows: command-line execution for CI pipelines and programmatic invocation for custom automation.

Command-Line Interface

The main() function in license_checker.py uses argparse to expose a comprehensive CLI. You can scan a project root directly or supply a pre-generated Software Bill of Materials (SBOM).

# Analyze the current repository with human-readable output

python engineering/dependency-auditor/scripts/license_checker.py . \
    --format text \
    --policy strict \
    --warn-conflicts

Key flags include:

• --format: Selects text for console-friendly reports or json for machine parsing.
• --policy strict: Enforces a compliance threshold (score below 80 exits with status 1).
• --warn-conflicts: Forces exit code 2 when any license conflict is detected, enabling CI gates to block merges.
• --inventory: Accepts a path to a pre-generated JSON dependency file instead of scanning package.json directly.

Programmatic Usage

For custom workflows, instantiate LicenseChecker and call analyze_project():

from pathlib import Path
from engineering.dependency-auditor.scripts.license_checker import LicenseChecker

checker = LicenseChecker()
result = checker.analyze_project(Path("/my/project"))

print(result["compliance_score"])        # Numeric score 0-100

print(result["conflicts"])               # List of LicenseConflict objects

print("\n".join(result["recommendations"]))  # Actionable remediation advice

The analyze_project() method returns a rich dictionary containing the detected project license, dependency license resolutions, a summary distribution, flagged conflicts, and scored recommendations.

Working with Pre-Generated Inventories

If your organization already generates dependency inventories via external SBOM tools, bypass the built-in scanner using _load_dependency_inventory():

python engineering/dependency-auditor/scripts/license_checker.py . \
    --inventory path/to/deps.json \
    --format json \
    > compliance-report.json

This JSON output integrates directly with dashboards, policy-enforcement bots, or legal review workflows.

Understanding the Compliance Report

The generate_report() method formats audit results into structured sections: a high-level summary, license distribution statistics, explicit conflict listings, high-risk dependencies, and prioritized recommendations. When --format text is selected, the report renders console-friendly tables; when --format json is selected, the output becomes a parseable object containing the same semantic data.

Because the tool uses only Python’s standard library, it remains portable across any environment where Claude Skills is installed, from developer laptops to locked-down CI runners. Adding support for additional ecosystems—such as Python requirements.txt or Go go.mod—requires implementing a new scanner that returns the list-of-dicts structure expected by _analyze_dependency_license(), without altering the core checker logic.

Summary

• The LicenseChecker class in engineering/dependency-auditor/scripts/license_checker.py provides a pure-Python engine for dependency auditing and license compliance checking.
• It combines a canonical license database (SPDX identifiers), a compatibility matrix, and regex pattern detection to resolve license ambiguities.
• The CLI supports strict policy enforcement with non-zero exit codes for CI/CD integration, while the Python API allows programmatic analysis via analyze_project().
• The tool accepts both live project scans (e.g., package.json) and pre-generated JSON inventories via the --inventory flag.
• Supporting files such as dep_scanner.py, upgrade_planner.py, and license_compatibility_matrix.md provide extension points for multi-ecosystem support and security-risk analysis.

Frequently Asked Questions

What license formats does the tool recognize?

The checker recognizes standard SPDX identifiers (e.g., MIT, Apache-2.0, GPL-2.0) through its internal database built by _build_license_database(). For non-standard declarations, it employs _detect_license_from_text() with regex patterns constructed in _build_license_patterns() to match common license boilerplate inside plain-text files.

How does the compliance scoring work?

The analyze_project() method calculates a numeric compliance score between 0 and 100 based on the ratio of permissive versus copyleft licenses, detected conflicts, and risk-weighted obligations. When the CLI runs with --policy strict, the tool exits with status 1 if the score falls below 80, preventing releases that fail organizational standards.

Can I integrate this into CI/CD pipelines?

Yes. The main() entry point returns specific exit codes for automation: status 1 for strict policy violations (low compliance scores) and status 2 for detected conflicts when --warn-conflicts is enabled. These codes allow build systems to gate merges, trigger legal review workflows, or generate artifacts for compliance dashboards.

How do I add support for other package managers?

Extending the tool requires implementing a new scanner function that returns the same list-of-dicts structure consumed by _analyze_dependency_license(). Because LicenseChecker isolates ingestion logic from analysis logic, you can add Python requirements.txt or Rust Cargo.toml support by modifying dep_scanner.py or creating a new module without touching the core compatibility engine in license_checker.py.

{
  "mcpServers": {
    "instagit": {
      "command": "npx",
      "args": ["-y", "instagit@latest"]
    }
  }
}