Trust Assessment
material-tracker received a trust score of 79/100, placing it in the Mostly Trusted category. This skill has passed most security checks with only minor considerations noted.
SkillShield's automated analysis identified 2 findings: 0 critical, 1 high, 1 medium, and 0 low severity. Key findings include Missing required field: name, Unrestricted file write via user-controlled path.
The analysis covered 4 layers: Manifest Analysis, Static Code Analysis, Dependency Graph, LLM Behavioral Safety. All layers scored 70 or above, reflecting consistent security practices.
Last analyzed on February 13, 2026 (commit 13146e6a). SkillShield performs automated 4-layer security analysis on AI skills and MCP servers.
Layer Breakdown
Behavioral Risk Signals
Security Findings2
| Severity | Finding | Layer | Location | |
|---|---|---|---|---|
| HIGH | Unrestricted file write via user-controlled path The `export_to_excel` function directly uses the `output_path` argument without validation or sanitization. This allows an attacker to specify an arbitrary file path on the system where the skill is executed. This could lead to overwriting critical system files, writing data to unintended or sensitive locations, or potentially data exfiltration if the path points to a network share or a publicly accessible directory. Implement strict validation and sanitization of the `output_path` argument. Ensure the path is confined to a secure, designated output directory (e.g., a temporary directory or a project-specific output folder) and does not allow directory traversal (e.g., `../`). Consider returning the file content directly or using a sandboxed file system if available, rather than writing to a user-specified path. | LLM | SKILL.md:270 | |
| MEDIUM | Missing required field: name The 'name' field is required for claude_code skills but is missing from frontmatter. Add a 'name' field to the SKILL.md frontmatter. | Static | skills/datadrivenconstruction/material-tracker/SKILL.md:1 |
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