This MongoDB OSHA server has three tools with basic but incomplete definitions. All tools have descriptions and input schemas present, but the descriptions are generic and lack depth. Parameter descriptions are minimal. Output schemas are not documented anywhere in the provided source. The tools follow a reasonable verb_noun naming convention (search_*, get_*), but the descriptions do not explain WHEN to use one tool vs another, what the output structure is, or any error recovery guidance. Tool parameters lack detail about valid ranges, formats, or dependencies. The server shows basic implementation quality but falls short of production-grade agent tooling standards.

• Document output schemas for all three tools. Declare the expected response structure (e.g., search_osha_rules returns { results: [{ rule_id, database, similarity_score, rule_data: { identifier, label, label_description, ... } }] }) so agents know what fields to expect.
• Add parameter constraints and format descriptions. For identifier, add: '(pattern: ^[0-9A-Z]+$, length 1-20)'. For limit, add: 'integer, 1-100, default 10'. For database, the enum is good but add in description: 'Searches both health and construction rules by default; use "health" or "construction" to limit scope.'
• Clarify tool purpose and selection. In search_osha_rules description, add: 'Use this for natural language queries like "electrical hazards" or "fall protection". For structured rule codes, use search_by_identifier.' In search_by_identifier, add: 'Use this when you have a partial rule ID like "1910" or "A". For full-text semantic search, use search_osha_rules.'
• Document error cases and recovery. Add to descriptions: 'Returns empty list if no rules match or no vectors found. If query is too short (under 3 chars), may return broad results.' Document what get_rule_details returns if rule_id not found (empty, null, error message?).
• Add response field documentation. Example: 'Each result includes rule_id (string), database ("health"|"construction"), and similarity_score (0.0-1.0). The rule_data field contains identifier, label, label_description, type, parent_path, and children_identifiers.'
• Consider exposing similarity_threshold as an optional parameter in search_osha_rules, with description: 'Minimum cosine similarity (0.0-1.0, default 0.1). Lower values return broader results; higher values return only very close matches.'