Trust Assessment
cwicr-quantity-matcher 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, Arbitrary File Write via output_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 14, 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 | Arbitrary File Write via output_path The `export_matches` function allows writing an Excel file to an arbitrary `output_path` provided by the user. An attacker could exploit this to overwrite critical system files, write sensitive data to an accessible location, or potentially write malicious executable files if the agent runs with elevated privileges and the path is not properly validated. This grants excessive write permissions to the skill. Restrict the `output_path` to a designated, sandboxed directory. Implement strict validation of the `output_path` to prevent directory traversal (e.g., `../`) or absolute path manipulation. Consider returning the generated Excel data directly to the user/LLM instead of writing to the filesystem, or requiring explicit user confirmation for file writes outside a designated safe area. | LLM | SKILL.md:306 | |
| 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/cwicr-quantity-matcher/SKILL.md:1 |
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