This server has severe definition quality issues. 30 tools are defined, but most lack proper schemas, descriptions are in Turkish and often vague, and parameter documentation is minimal. Tool names are inconsistent (mix of verb_noun and generic patterns). No input schemas are visible in the provided code for most tools, only brief descriptions. Error handling is absent. The server appears to be a Gradio UI wrapper around agent implementations rather than a proper MCP server with structured tool definitions.

• Translate all tool descriptions to English and expand to 100-200 characters. Include WHAT the tool does, WHEN to use it, and WHAT it returns. Example: 'Analyzes CV data against company requirements and returns a structured gap report with missing skills, matching projects, and recommendations for improvement.'
• Define explicit JSON Schema for every tool input. Include type, description, and constraints for each parameter. Example: {"cv_data": {"type": "object", "description": "CV object with keys: name, skills (array), projects (array)", "required": ["skills"]}}
• Document output schemas for all tools. Specify the structure of returned objects, field types, and what IDs/references are included for chaining. Example: 'Returns {gap_analysis: string, missing_skills: [string], match_score: number (0-100)}'
• Add error handling guidance to tool descriptions. State what errors can occur and what the LLM should do. Example: 'If CV data is invalid, returns {error: string, suggestion: string}. Retry with corrected CV structure.'
• Rename generic tools: 'think' → 'analyze_situation', 'act' → 'execute_action', 'observe' → 'evaluate_result'. Rename 'cv_tool' → 'analyze_cv_langchain', 'company_tool' → 'research_company_langchain' to disambiguate from primary tools.

Inferred effective spec: <=2025-11-25.

• Relies on Logging (deprecated) - log to stderr or use OpenTelemetry