SkillGuard exposes a single security-scanning tool with a clear, well-motivated purpose. The tool name 'scan_skill' is verb-first and unambiguous. The description (287 chars) is detailed and explains what the tool does, when to use it, and what it returns, well above the 10-char minimum and within the 194-char baseline average. The input schema is present with a 'target' parameter that has a type (string) and description. However, the schema lacks formal constraints (no enum, pattern, or minLength/maxLength), and there is no documented output schema, the description mentions 'returns a verdict (clean/suspicious/dangerous) with the flagged files' but the actual response structure is not formally specified. Error handling is not visible in the provided code excerpt. The tool is READ_ONLY (no state mutation), which is appropriate for a scanner.

• Document the output schema explicitly. Define the response structure: e.g., { verdict: 'clean'|'suspicious'|'dangerous', flagged_files: [{file: string, rule_id: string, severity: 'warn'|'danger', message: string}], summary: string }. This enables LLMs to extract and act on results.
• Add JSON Schema constraints to the 'target' parameter: minLength, maxLength, and a pattern regex to validate git URLs and local paths. Replace the example values with formal constraints.
• Implement and document error handling. Return structured error responses with actionable guidance: { error: string, code: 'git_clone_failed'|'invalid_path'|'timeout', suggestion: string }. Guide the LLM on retry or alternative actions.
• Add the readOnlyHint annotation to the tool definition to declare that scan_skill does not mutate state. This enables clients to optimize caching and retry logic.
• Migrate from STDIO to Streamable HTTP transport to enable remote accessibility and compatibility with hosted MCP clients. STDIO limits deployment to local/container scenarios.