Trust Assessment
progress-photo-analyzer received a trust score of 87/100, 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, 0 high, 2 medium, and 0 low severity. Key findings include Missing required field: name, Unrestricted file write via export_report function.
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 | |
|---|---|---|---|---|
| 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/progress-photo-analyzer/SKILL.md:1 | |
| MEDIUM | Unrestricted file write via export_report function The `export_report` function allows writing an Excel file to an arbitrary `output_path` provided by the user. If the skill's execution environment is not properly sandboxed, this could lead to overwriting sensitive files, writing to unauthorized locations, or potentially contributing to data exfiltration if the path points to an external or public location. Implement strict validation or sandboxing of `output_path` in the calling environment. Ensure the sandbox restricts file system writes to designated directories. Alternatively, the skill could enforce a limited set of allowed output directories or only accept relative paths within a secure working directory. | LLM | SKILL.md:292 |
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