decision-tree-analysis
Use when building a decision tree model in R and generating feature importance ranking outputs. Supports classification and regression, automatic task detection, parameter validation, model evaluation summaries, and exports of feature-importance tables and figures.
71
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Low
Low-risk findings worth noting
Low
Low-risk findings.
2 low severity findings. Worth noting, but not necessarily harmful.
W011: Third-party content exposure detected (indirect prompt injection risk).
What this means
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
Why it was flagged
The workflow reads tabular data files via data.table::fread based on user arguments, meaning arbitrary outsider-authored CSV/TXT files can be ingested if provided as input.
W012: Unverifiable external dependency detected (runtime URL that controls agent).
What this means
The skill fetches instructions or code from an external URL at runtime, and the fetched content directly controls the agent’s prompts or executes code. This dynamic dependency allows the external source to modify the agent’s behavior without any changes to the skill itself.
Why it was flagged
The R script uses an external URL (https://cloud.r-project.org) at runtime via `install.packages()` to fetch and install required R package dependencies necessary for code execution.
- Repository
- aipoch/medical-research-skills
- Commit
f5ef65b
- Audited
- Security analysis
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