Solar Human Proofreader demonstrates solid definition quality with complete schemas, detailed descriptions, and thoughtful parameter design. All 6 tools have explicit Zod schemas with type definitions and descriptions. Tool names are action-oriented (proofread, read_through, readability, compare, suggest, usage). Descriptions are substantive (100-300+ chars) and explain WHEN to use each tool. Parameters include enums, constraints, and helpful defaults. However, output schemas are not formally documented in the code, responses are rendered as formatted text strings rather than structured objects. Error handling is present but generic. Tool composition is clean with single responsibilities.

• Define explicit output schemas for each tool. Instead of returning formatted text, return structured objects: {score: number, grade: string, notes: string[], hardSentences: {reason, text}[]} for readability; {before: string, after: string, changeRate: number, fidelityChecks: {passed: boolean, detail: string}[]} for compare. Document these in tool descriptions.
• Enhance error handling with categorization. Wrap ProviderError and QuotaExceededError with metadata: {error: string, category: 'retryable'|'user_fixable'|'fatal', suggestion: string}. Guide LLMs on recovery actions.
• Rename 'read_through' to 'diagnose_readability' or 'analyze_readability_issues' to reduce confusion with 'readability'. Make the distinction explicit: diagnose = qualitative feedback; readability = quantitative metrics.
• Add optional limit and offset parameters to readability and compare to support pagination. Document max result sizes in descriptions (e.g., 'Returns up to 6 hard sentences').
• Document the response structure for 'usage' tool. Clarify what fields are returned (e.g., calls_today, remaining_quota, provider_type) so LLMs know how to interpret the output.