Trust Assessment
submittal-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, Arbitrary File Write via export_log.
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 export_log The `export_log` method allows writing an Excel file to an arbitrary `output_path` provided by the caller. This constitutes an arbitrary file write vulnerability. An attacker could specify a path to a sensitive location, potentially overwriting system files (leading to denial of service) or writing skill-generated data to an attacker-controlled directory for exfiltration, depending on the execution environment's permissions. Restrict the `output_path` to a predefined, sandboxed directory. Implement strict path validation to ensure the output file is written only to an allowed location, preventing directory traversal attacks. For example, prepend a secure base directory to the provided `output_path` or only allow a filename within a designated export folder. | LLM | SKILL.md:109 | |
| 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/submittal-tracker/SKILL.md:1 |
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