Four tools with clear, actionable descriptions (avg 156 chars, within baseline 194). All have input schemas with proper types and enums. However, naming lacks action verbs (scope, status, inspect_definition, check_now are descriptive but not verb-noun patterns). Parameter descriptions are present but minimal. No output schemas documented. Error handling guidance absent. Tools are read-only (low risk) but lack recovery patterns.

• Rename tools to verb-noun patterns: scope → get_scope, status → check_conformance_status, inspect_definition → analyze_tool_definition, check_now → run_conformance_check. This aligns with 90% of A+ tools and helps LLMs parse intent from names alone.
• Document output schemas for all tools. E.g., check_now returns {findings: [{type, severity, message}], duration_seconds, sandbox_status}. This enables LLMs to extract and chain results.
• Add error handling guidance to check_now: 'May fail with timeout (retryable after 30s), Docker unavailable (fatal, check server setup), or package not found (user-fixable, verify registry and name).'
• Expand parameter descriptions with format/constraint hints. E.g., purl: 'Package URL in format pkg:npm/package-name or pkg:pypi/package-name (e.g., pkg:npm/express)'. definition: 'JSON object with keys: name (string), description (string), inputSchema (JSON Schema object).'
• Add tool annotations to schema: mark check_now with destructiveHint=true (runs untrusted code) and idempotentHint=false (side effects in sandbox). This signals to agents that retries may have consequences.