Where to Find Helper Scripts for Executing Anthropic Cybersecurity Skills

The mukul975/Anthropic-Cybersecurity-Skills repository bundles ready-to-run helper scripts in the top-level tools/ directory and within each skill’s scripts/ subfolder, with agent.py serving as the primary execution entry point.

The mukul975/Anthropic-Cybersecurity-Skills repository organizes its automation logic through dedicated helper scripts for executing Anthropic Cybersecurity Skills. These utilities are partitioned into repository-wide validation tools and per-skill execution agents that handle specific cybersecurity analysis tasks. Every skill follows a consistent directory pattern that makes locating and running these scripts predictable across the collection.

Repository Structure for Helper Scripts

The helper scripts reside in two distinct locations, each serving a different scope of operation.

Top-Level Tools Directory

The tools/ directory at the repository root contains generic utilities that operate across the entire skill collection. The primary file here is tools/validate-skill.py, a Python script that checks each SKILL.md file for required metadata fields, proper name formatting, description length constraints, and allowed subdomains or tags.

Per-Skill Scripts Subdirectory

Every individual skill includes a scripts/ folder nested within its directory structure. According to the repository layout, these paths follow the pattern skills/<skill-name>/scripts/ and contain:

• agent.py – The primary execution entry-point that performs the actual analysis described by the skill definition.
• process.py (optional) – An auxiliary helper for batch processing or pipeline execution when a skill requires handling multiple inputs.

Key Helper Scripts and Their Functions

Understanding the specific function of each script type ensures you invoke the correct utility for your task.

tools/validate-skill.py serves as the central validation gate. It reads the SKILL.md files located in individual skill directories and verifies that all required frontmatter fields are present and correctly formatted.

skills/<skill-name>/scripts/agent.py acts as the concrete analysis engine. For example, skills/analyzing-ransomware-payment-wallets/scripts/agent.py queries blockchain APIs, validates cryptocurrency addresses, and produces JSON forensic reports based on the skill’s defined logic.

skills/<skill-name>/scripts/process.py provides a secondary interface for batch operations. This script appears only in skills that support bulk processing, accepting input files containing multiple targets rather than single command-line arguments.

How to Execute the Helper Scripts

All scripts require only a recent Python 3 interpreter and use the standard library, with the single external dependency requests imported lazily (the script will print an informative error message if requests is missing when attempting API calls).

Validate Skill Metadata

Run the validator against a specific skill directory or the entire repository:

# Validate a specific skill

python tools/validate-skill.py skills/analyzing-ransomware-payment-wallets/

# Validate every skill in the repository

python tools/validate-skill.py --all

Run a Skill Agent

Execute the primary analysis logic by invoking agent.py directly with the required arguments:

# Analyze a specific Bitcoin address using the ransomware wallet skill

python skills/analyzing-ransomware-payment-wallets/scripts/agent.py 12t9YDPgwueZ9NyMgw519p7AA8isjr6SMw

The script outputs a short summary to stdout and writes a full JSON report containing the forensic analysis results.

Batch Processing with process.py

When available, use the processing helper for pipeline execution:

# Process multiple addresses from an input file

python skills/analyzing-ransomware-payment-wallets/scripts/process.py input_list.txt

Dependencies and Environment Setup

The helper scripts for executing Anthropic Cybersecurity Skills maintain minimal dependencies to ensure portability. You need:

• Python 3 – Any recent version capable of running standard library modules.
• requests – Required only for skills that query external APIs (such as blockchain explorers), and imported lazily so the script fails gracefully with a descriptive message if the package is absent.

No secret configuration files or environment variables are required to run the basic validation and execution scripts, though individual skill agents may require API keys for external data sources depending on the specific cybersecurity analysis being performed.

Summary

• Helper scripts live in tools/ (repository-wide) and skills/<name>/scripts/ (per-skill).
• tools/validate-skill.py checks metadata compliance for all SKILL.md files.
• agent.py is the primary execution script for running a specific skill’s analysis logic.
• process.py offers optional batch processing capabilities where supported.
• All scripts run with standard Python 3 and require only the requests package for API-dependent skills.

Frequently Asked Questions

Where exactly are the helper scripts located in the repository?

The helper scripts are located in two places: the tools/ directory at the repository root contains validation utilities like validate-skill.py, while each skill directory contains a scripts/ subfolder with agent.py (required) and optionally process.py. For example, the ransomware wallet analysis scripts reside at skills/analyzing-ransomware-payment-wallets/scripts/.

What is the difference between agent.py and process.py?

agent.py is the primary execution script that performs the core analysis logic defined by the skill, typically accepting individual targets via command-line arguments. process.py serves as an optional batch processing interface that accepts input files containing multiple targets, designed for pipeline integration and bulk operations.

Do I need API keys to run these scripts?

The helper scripts themselves require no authentication to run basic validation or local processing. However, specific skill agents like skills/analyzing-ransomware-payment-wallets/scripts/agent.py query external blockchain APIs, which may require API keys depending on the data provider’s rate limiting and access policies.

How do I validate that a skill is configured correctly?

Run python tools/validate-skill.py skills/<skill-name>/ to check that the skill’s SKILL.md metadata file contains all required fields, proper formatting, and compliant tag structures. Use the --all flag to validate every skill in the repository simultaneously.

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