Trust Assessment
cash-flow-forecaster 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_forecast method.
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 | Arbitrary file write via export_forecast method The `export_forecast` method allows writing an Excel file to any path specified by the `output_path` argument. If this argument is controlled by an untrusted source, an attacker could use path traversal techniques (e.g., `../../../../etc/passwd`) to write to arbitrary locations on the filesystem, potentially overwriting critical system files, writing to sensitive directories, or exfiltrating data by writing to a controlled network share. This grants excessive permissions to the skill's file system access. Implement robust path validation and sanitization for the `output_path` argument. Restrict file writes to a designated, sandboxed directory (e.g., a temporary directory or a user-specific output folder). Ensure the path does not contain directory traversal sequences (e.g., `../`) and only allows writing to intended file types and locations. | 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/cash-flow-forecaster/SKILL.md:1 |
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