// Example skill demonstrating secure file reference resolution with supporting files
Extract and convert PDF documents using Python scripts
Test skill with executable scripts for testing script execution feature
Parse and analyze CSV files with data validation
Parse and validate JSON data with schema support
Example skill demonstrating nested directory structure at depth 2
Example skill demonstrating nested directory structure at depth 3
| name | file-reference-skill |
| description | Example skill demonstrating secure file reference resolution with supporting files |
| allowed-tools | [] |
This skill demonstrates how to use supporting files (scripts, templates, documentation) within a skill directory.
This skill uses helper scripts and templates for data processing. All supporting files are accessible via relative paths from the skill's base directory.
scripts/data_processor.py - Main data processing scriptscripts/validator.py - Input validation utilitiesscripts/helper.sh - Shell helper scripttemplates/config.yaml - Configuration templatetemplates/report.md - Report generation templatedocs/usage.md - Detailed usage instructionsdocs/examples.md - Example use casesWhen this skill is invoked with arguments, it can access supporting files using the FilePathResolver:
from pathlib import Path
from skillkit.core.path_resolver import FilePathResolver
# Get the skill's base directory (injected by BaseDirectoryProcessor)
base_dir = Path("<base_directory_from_context>")
# Resolve supporting files securely
processor_script = FilePathResolver.resolve_path(base_dir, "scripts/data_processor.py")
config_template = FilePathResolver.resolve_path(base_dir, "templates/config.yaml")
usage_docs = FilePathResolver.resolve_path(base_dir, "docs/usage.md")
# Read file contents
with open(processor_script) as f:
script_code = f.read()
The skill expects data file paths as arguments:
Example invocation: file-reference-skill data/input.csv data/output.csv
Processing steps:
scripts/validator.pyscripts/data_processor.pytemplates/report.md