14 tools with mostly complete schemas and descriptions, but significant gaps in parameter documentation and error handling guidance. Tool names follow verb_noun convention well (get_, verify_, map_, lookup_, analyze_, classify_, match_, search_, list_, align_, evaluate_, sanitize_). Descriptions range 50-180 chars, meeting baseline minimums. However, many parameters lack type constraints (enums, ranges), and output schemas are not documented. No error recovery guidance visible. The sanitize_pii tool is well-named but lacks input validation details. Overall: solid foundation, but falls short of production-grade polish expected for A-tier tools.

• Document output schema for every tool. Specify field names, types (string, number, array, object), and what each field represents. Example: get_phonics_scope returns {phonemes: string[], graphemes: string[], heart_words: string[], grade: string, unit: string}.
• Add enum constraints to grade_level (K, 1, 2, 3, 4, 5), unit (1-6 or similar), state (GA, CA, TX, etc.), and tool_type (screener, diagnostic, progress_monitoring, outcome). Replace free-form strings with validated choices.
• Add error handling documentation. Specify what errors each tool can return (e.g., 'Invalid grade level', 'Text too long', 'State not found') and recovery steps (e.g., 'Try search_evidence with a broader topic').
• For sanitize_pii, document the input object schema: which fields are scanned for PII (name, email, student_id, ssn, etc.), what anonymization rules apply, and what the output structure is.
• Add pagination to list_frameworks and list_assessments: accept limit (default 20, max 100) and offset parameters; return {items: [...], total: number, limit: number, offset: number}.