Single tool with minimal definition quality. Tool name 'query_feature_suggestions' is descriptive but the schema is severely incomplete. Input parameter 'limit' has a type (number) and basic description, but lacks constraints (min/max bounds). No output schema is documented, the tool returns JSON text without specifying field structure, making it impossible for LLMs to plan downstream operations. Error handling returns plain text rather than structured guidance. The tool description (18 chars) is below the 34-char baseline minimum and provides no context on when to use it or what it returns.

• Expand tool description to 100-200 chars: 'Retrieve feature suggestions from the database. Returns a list of all submitted feature requests with metadata. Use this to discover what features users have requested. Limit defaults to 100 records.'
• Add numeric constraints to 'limit' parameter: min=1, max=1000, default=100. Document in description: 'Maximum number of records to return (1-1000, default 100).'
• Document output schema explicitly. Define return structure: {content: [{type: 'text', text: JSON.stringify([{id, title, description, votes, created_at}, ...])}]}. Specify field types and meanings.
• Implement pagination: add 'offset' parameter (default 0), return 'total_count' and 'has_more' in response so LLM can fetch subsequent pages.
• Enhance error handling with recovery guidance: 'Error querying feature_suggestions: [reason]. Verify Supabase credentials are set. Retry with a smaller limit if timeout occurs.'

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

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