PRD Mastery: Context-Aware, Expert-Driven, and Token-Efficient Refinement

The skill was analyzed across all 9 threat categories with an 'assume-malicious' posture. No prompt injection, data exfiltration, obfuscation, privilege escalation, persistence mechanisms, or time-delayed/conditional attacks were detected. The two Node.js scripts, create_prd.js and repo_scan.js, utilize standard Node.js fs and path modules for local file system interactions. They do not introduce external, unverifiable dependencies. Input validation for featureName in create_prd.js is handled by toKebabCase for file naming, and the content is written to files, not executed. The repo_scan.js script reads common project configuration files within the current working directory and outputs a summary to a local markdown file; it does not attempt to access sensitive credential files or perform network operations. The documentation files are static and contain no executable code or malicious patterns. While the output of repo_scan.js (e.g., prelim_summary.md) or user-generated PRDs could theoretically contain content that an LLM might misinterpret (indirect prompt injection), this is an inherent risk of an LLM processing any external data and not a vulnerability introduced by the skill's scripts themselves. The scripts are well-contained and perform their intended functions safely.