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egarcia74

Warp SQL Server MCP

by egarcia74

get_optimization_insights

Analyze SQL Server database performance and health to identify optimization opportunities. Provides insights on query efficiency, resource usage, and configuration improvements.

Instructions

Get comprehensive database optimization insights and health analysis

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
databaseNoDatabase name (optional)
analysis_periodNoAnalysis time period: 24_HOURS, 7_DAYS, 30_DAYS (optional, defaults to 7_DAYS)

Implementation Reference

  • Defines the input schema and metadata for the get_optimization_insights tool.
    {
      name: 'get_optimization_insights',
      description: 'Get comprehensive database optimization insights and health analysis',
      inputSchema: {
        type: 'object',
        properties: {
          database: {
            type: 'string',
            description: 'Database name (optional)'
          },
          analysis_period: {
            type: 'string',
            description:
              'Analysis time period: 24_HOURS, 7_DAYS, 30_DAYS (optional, defaults to 7_DAYS)',
            enum: ['24_HOURS', '7_DAYS', '30_DAYS']
          }
        }
      }
    },
  • index.js:240-242 (registration)
    Registers the tool in the MCP server's tool list via getAllTools() from tool-registry.
    // Register tools from the tool registry
    this.server.setRequestHandler(ListToolsRequestSchema, async () => ({
      tools: getAllTools()
  • Dispatch handler in the main tool switch statement that invokes the specific optimization insights method.
    case 'get_optimization_insights':
      return {
        content: await this.getOptimizationInsights(args.database)
      };
  • Primary handler method that delegates to QueryOptimizer and formats the response for MCP.
    async getOptimizationInsights(database) {
      try {
        const insights = await this.queryOptimizer.getOptimizationInsights(database);
        return [
          {
            type: 'text',
            text: JSON.stringify(
              {
                success: true,
                data: insights
              },
              null,
              2
            )
          }
        ];
      } catch (error) {
        throw new McpError(ErrorCode.InternalError, error.message);
      }
    }
  • Core QueryOptimizer implementation for getOptimizationInsights (currently a placeholder).
    async getOptimizationInsights(query) {
      const pool = this.connectionManager.getPool();
      if (!pool) {
        throw new Error('Not connected to any server');
      }
    
      if (!query) {
        throw new Error('Query is required for getOptimizationInsights');
      }
    
      // Placeholder for actual implementation
      return Promise.resolve({});
    }
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden for behavioral disclosure. While 'Get comprehensive database optimization insights' implies a read-only analysis operation, it doesn't specify what 'comprehensive' includes, whether it requires specific permissions, if it's resource-intensive, or what format the insights are returned in. Significant behavioral context is missing.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that gets straight to the point without unnecessary words. It's appropriately sized for a tool with two optional parameters and no complex behavioral requirements to explain.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with no annotations, no output schema, and multiple similar sibling tools, the description is insufficient. It doesn't explain what 'comprehensive insights' include, how they differ from other performance/analysis tools, what format results are returned in, or any behavioral characteristics like execution time or resource requirements.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has 100% description coverage, so the baseline is 3. The tool description doesn't add any parameter-specific information beyond what's already documented in the schema (database name and analysis period with defaults/enums). No additional context about parameter interactions or usage patterns is provided.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with specific verbs ('Get comprehensive database optimization insights and health analysis'), identifying it as a read operation that provides analysis. However, it doesn't explicitly differentiate from siblings like 'get_performance_stats' or 'get_query_performance' which might offer overlapping functionality.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. With multiple sibling tools like 'get_performance_stats', 'analyze_query_performance', and 'detect_query_bottlenecks', there's no indication of what makes this tool distinct or when it should be preferred over similar options.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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