Trust Assessment
codebase-documenter received a trust score of 92/100, placing it in the Trusted category. This skill has passed all critical security checks and demonstrates strong security practices.
SkillShield's automated analysis identified 2 findings: 0 critical, 0 high, 1 medium, and 1 low severity. Key findings include Node lockfile missing, Untrusted Input Reflected Without Sanitization.
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 | Untrusted Input Reflected Without Sanitization The `index.js` skill function directly returns the `input` it receives without any processing, validation, or sanitization. If the `input` contains malicious instructions (e.g., prompt injection attempts) or sensitive data, this reflection could enable prompt injection against the host LLM or unintended data exposure if the skill's output is subsequently processed by other systems. The `TODO` comment indicates that actual logic is missing, making the skill a simple passthrough. Implement proper input validation and sanitization before returning or using any part of the `input`. Ensure that sensitive information is not echoed and that potential prompt injection attempts are neutralized or filtered, especially if the skill's output is intended for further LLM processing. | LLM | index.js:5 | |
| LOW | Node lockfile missing package.json is present but no lockfile was found (package-lock.json, pnpm-lock.yaml, or yarn.lock). Commit a lockfile for deterministic dependency resolution. | Dependencies | skills/veeramanikandanr48/codebase-documenter/package.json |
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