Four tools with complete JSON schemas and descriptions. Naming follows verb_noun pattern (get_*, compare_*, list_*). Descriptions are substantive (150-250 chars), explaining what data is returned and sourcing. However, parameter descriptions lack actionable constraints (ranges, formats, dependencies). No error handling guidance. Output schemas are not documented, LLMs cannot predict response structure. No tool annotations (readOnlyHint present in metadata but not in schema). Composition is sound: each tool has one responsibility, and tools chain naturally (list_industry_sources supports the others). Security is strong: read-only operations, no secrets, no state mutation.

• Document output schemas for all four tools. Example for get_agency_cost_benchmark: '{"operating_models": [{"model": "chatter_only", "headcount": 2.2, "monthly_cost_usd": 12500, "sources": ["vice_2023", ...]}], "assumptions": {...}}'.
• Expand parameter descriptions with constraints and rationale. E.g., 'creator_count (1 - 50): Agencies beyond 50 creators typically split into multi-team structures. Benchmark assumes single-team operations.'
• Add error handling guidance. E.g., 'If operating_model is invalid, returns error with valid options: chatter_only, assisted_ai, autonomous_ai, all. If avg_revenue_per_creator_usd < 1000, returns warning that benchmark assumes minimum viable creator earnings.'
• Add readOnlyHint and idempotentHint annotations to tool schemas. All four tools are read-only and idempotent, make this explicit so LLMs know they are safe to retry.
• For compare_of_tooling, clarify behavior when 'tools' array is empty or contains invalid names. E.g., 'If tools array is empty, returns all 8 competitors. If a tool name is not recognized, skips it and returns available matches.'