The server defines 8 tools with complete Zod schemas and descriptions. However, there are systematic quality gaps: (1) Tool names lack clear action verbs, 'analyze_competitors', 'industry_research', 'swot_analysis' read more as nouns or descriptive phrases than imperative actions; (2) Descriptions are present but generic, averaging ~150 chars with minimal context on WHEN to use each tool or what differentiates it from similar tools; (3) Pro-tier tools are gated at runtime but not clearly marked in schema or naming, forcing the LLM to discover tier requirements via error messages; (4) Output schemas are NOT documented, we see Zod input validation but no description of what fields clients should expect in responses; (5) Error handling is minimal, the code shows tier-gating errors but no guidance for recovery or actionable next steps; (6) Tool composition is weak, many tools appear to overlap (analyze_competitors vs swot_analysis both analyze a business; industry_research vs market_trends both study industries), yet there is no clear guidance on which to call when. On the positive side: all tools have input schemas with types and descriptions, parameter constraints are reasonably explicit (e.g., 'format: url' for website_url), and there are no missing required parameters in the visible definitions.

• Rename tools to use imperative action verbs: 'analyze_competitors' → 'analyze_competitor_landscape'; 'industry_research' → 'research_industry'; 'swot_analysis' → 'generate_swot_analysis'; 'market_trends' → 'track_market_trends'; 'customer_persona' → 'build_customer_persona'; 'pricing_analysis' → 'analyze_pricing_strategy'; 'local_market_analysis' → 'analyze_local_market'; 'business_plan_section' → 'generate_business_plan_section'. Ensure each name starts with a verb that reflects the action.
• Document output schemas for all tools. Specify what fields the response contains, their types, and examples. For example: analyze_competitors should return { competitors: [{ name, market_share, strengths, weaknesses }], recommendations: string, market_size: number }. This lets LLMs chain results into follow-up calls.
• Add recovery guidance to error responses. When a tool is not available due to tier limits, return: '🔒 This tool requires a Pro subscription. Alternatives: (1) Upgrade at https://mcp.ezbizservices.com/pricing, or (2) Use the free-tier tool [X] for similar insights.' This guides the agent toward actionable next steps.
• Clarify tool composition in descriptions. For each tool, add a 'Use this tool when:' section. Example for swot_analysis: 'Use this tool when you need a structured analysis of a business's internal strengths/weaknesses and external opportunities/threats. For competitive positioning only, use analyze_competitors instead.' This prevents tool confusion.
• Formalize enum constraints in Zod schemas. In business_plan_section, change the description-only list of section_type values to: z.enum(['executive_summary', 'market_analysis', 'operations', 'financial_projections', 'competitive_advantage', 'go_to_market', 'risk_analysis']). This is machine-readable and prevents hallucinated values.

Inferred effective spec: <=2025-11-25.

• Relies on Logging (deprecated) - log to stderr or use OpenTelemetry