Server has 4 tools with complete input schemas and descriptions, but quality is significantly hampered by Russian-language descriptions that are cryptic and domain-specific, making them difficult for LLMs to parse intent. Tool names are verb-based (search_, assess_, get_) which is good. However, descriptions are terse and assume deep trademark domain knowledge. Schemas are present with proper types and constraints (enums, minLength, defaults), but descriptions lack actionable guidance for LLM selection. No output schemas documented. Error handling is honest (refuses unavailable sources) but lacks recovery guidance. Overall: functional but not LLM-optimized.

• Translate all descriptions to English or provide English summaries. Current Russian descriptions are opaque to non-Russian-speaking LLMs. E.g., 'search_trademark: Paid search of Russian trademark registry (FIPS) by name. Requires FIPS client contract credentials. Returns matching trademarks with registration status.'
• Document output schemas for all tools. Add to server.py docstrings or README: 'search_trademark returns {results: [{number, name, status, classes}], total_count, has_more}' so LLMs know what fields to expect.
• Add recovery guidance to error responses. When source_not_configured is returned, append: 'To enable paid search, set MCP_TRADEMARKS_FIPS_LOGIN and MCP_TRADEMARKS_FIPS_PASSWORD environment variables.'
• Expand parameter descriptions with examples and constraints. E.g., 'classes: NICE classification codes (1-45). Example: [25, 35] for clothing and advertising. Leave empty to search all classes.'
• Add a tool annotation or parameter to clarify which tools require paid credentials vs which use free open registry. Consider a 'requires_paid_access' field in tool metadata or explicit naming (search_trademark_paid vs get_trademark_status_free).

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

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