Strong foundation with 18 well-named tools following verb_noun convention (resolve_, search_, list_, read_, get_). All tools have descriptions (avg 156 chars, within 10-1024 baseline). Input schemas present with type definitions and parameter descriptions. However, output schemas are not explicitly documented in the source code, responses are returned as pretty JSON but the structure is not formally specified. Error handling exists but lacks recovery guidance. Tool descriptions are concise and action-oriented, meeting the stage-one 160-char limit, but some parameter descriptions could be more detailed about constraints and formats.

• Document output schemas for all 18 tools. For each, specify the response object structure, field types, and pagination fields (if applicable). Example: 'Returns {"norms": [{"eli": string, "title": string, "sr": string}], "total": integer}'.
• Add recovery guidance to error responses. When a tool fails, include a suggestion: 'Language not available. Call fedlex.list_expressions() to see which languages this version supports.' This enables LLMs to self-correct.
• Convert parameter constraints to JSON Schema enums and bounds. Change 'lang' description to reference an enum constraint; add minValue/maxValue to 'limit' and 'max_chars' parameters. This makes constraints machine-parseable.
• Standardize pagination across all list/search tools. Ensure all tools that return multiple results support offset/limit and return a total count or next_cursor. Document pagination in tool descriptions.
• Add dependency hints to tool descriptions. For tools requiring 'eli' or 'eli_version', add: 'First call fedlex.resolve_sr() or fedlex.search_law() to obtain the ELI.' This guides multi-step planning.