Server has 15 tools with basic schemas and descriptions, but significant gaps prevent production use. Most tool descriptions are adequate (50-150 chars), but parameter descriptions are sparse or missing entirely. Input schemas exist but lack detail: many parameters have no type constraints, enums, or validation guidance. No output schemas documented. Error handling is absent, tools provide no recovery guidance. Tool naming follows verb_noun convention (good), but composition issues exist: call_code is dangerously broad (arbitrary Python execution), and several tools lack clear distinctions (e.g., simulate_model vs get_simulation_results). No security controls visible for destructive operations (restart_sysplorer, translate_model, simulate_model). STDIO transport caps protocol readiness at 50.

• Add output schemas to all tools. Document return types, field names, and structure. Example: simulate_model should return {result_file: string, status: 'success'|'failed', variables: {[name]: {values: number[], times: number[]}}}.
• Add enum constraints to parameters with known valid values. Example: translate_model target should be enum ['c', 'fmu', 'python']; plot_results plot_type should be enum ['line', 'scatter', 'bar'].
• Implement confirmation pattern for destructive tools. Add a 'confirm' parameter (boolean, default false) or split into preview + execute steps. Example: simulate_model with dry_run=true returns expected outputs without executing.
• Restrict call_code to a whitelist of safe operations or remove it entirely. If retained, add detailed description of allowed operations, timeout limits, and permission requirements. Consider splitting into domain-specific tools (e.g., run_model_analysis).
• Add error handling and recovery guidance. Every tool should return structured errors with actionable messages. Example: 'Model not found: "MyModel". Available models: [list]. Try load_model() first.' Implement pattern:recovery-guide.