BlinkAI Coworker exhibits severe definition quality gaps across all dimensions. Tool definitions are inferred from UI component files rather than explicit MCP server registration, capping individual tool scores at 50. Most tools (11/15) lack visible input schemas in the source code provided. Descriptions are present but generic and often under 50 characters. No output schemas documented. Error handling is absent. The server appears to be a desktop Electron app with embedded agent tools, not a proper MCP server with formal tool registration.

• Create explicit MCP server tool registration (e.g., in src/index.ts or src/server.ts) with formal tool definitions using @modelcontextprotocol/sdk. Move tool definitions out of UI components into server-side code.
• Add complete JSON Schema input definitions for all 15 tools. Include type, description, and constraints for every parameter. Example: mastra_workspace_execute_command should specify command as string with length limits and validation rules.
• For each tool, answer: What does it do? When should the LLM call it? What are prerequisites? Example: 'Execute a shell command in the workspace sandbox. Use for running scripts, builds, or system tasks. Returns stdout/stderr and exit code.'
• Document output schemas for all tools. Specify return type (object, array, string), required fields, and field types. Example: mastra_workspace_read_file should return {content: string, path: string, size: number, encoding: string}.
• Add error handling and recovery guidance. For destructive tools (delete, execute_command, write_file), implement dry-run support or confirmation patterns. Return actionable error messages: 'File not found at /path/to/file. Available files in /path: [list]. Did you mean one of these?'

Inferred effective spec: 2025-06-18+.

• Current-spec patterns present: structured tool output