Critical gaps across all dimensions. Tool names lack consistent verb prefixes (detect_ai_tools vs personalAgentsScanAll, inconsistent camelCase/snake_case). Descriptions present but generic; many lack actionable context for LLM selection. Input schemas visible but minimal, most tools accept only optional parameters with no type constraints. No output schemas documented. Error handling absent. Security concerns: tools read user files and capture conversations without explicit permission gates or audit trails. Composition issues: 8 tools (personalAgentsCapture*) do nearly identical work with no clear differentiation.

• Standardize naming to verb_noun snake_case (e.g., scan_personal_agents, capture_cursor_conversations, get_ai_tool_status). Ensure all tools start with action verbs.
• Consolidate the eight personalAgentsCapture* tools into a single capture_personal_agent_conversations(agent_type: enum, currentUser?: string) tool. Document the enum values and what each agent type returns.
• Document output schemas for all tools. Example: 'Returns array of {agent_type, conversation_id, title, timestamp, message_count}' for capture tools. Include pagination info if applicable.
• Add permission gates and audit logging. Require explicit user consent before reading local files. Log which agent called which tool with which parameters. Return clear errors when access is denied.
• Enhance parameter descriptions: specify type, format, constraints, and examples. E.g., 'currentUser (string, optional): User identifier or email. If omitted, uses system default. Format: email or UUID.'
• Add error handling with recovery guidance. E.g., 'File not found at ~/.cursor/conversations. Ensure Cursor is installed and has saved conversations.' instead of silent failures.