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create_index

Create database indexes on SQL Server tables to improve query performance by organizing data for faster retrieval and enforcing unique constraints when needed.

Instructions

Creates an index on a specified column or columns in an MSSQL Database table

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
columnsYesArray of column names to include in the index
indexNameYesName for the new index
isClusteredNoWhether the index should be clustered (default: false)
isUniqueNoWhether the index should enforce uniqueness (default: false)
schemaNameNoName of the schema containing the table
tableNameYesName of the table to create index on

Implementation Reference

  • The run method implements the core logic for creating an index on an MSSQL table using dynamic SQL query construction.
    async run(params: any) {
      try {
        const { schemaName, tableName, indexName, columns, isUnique = false, isClustered = false } = params;
    
        let indexType = isClustered ? "CLUSTERED" : "NONCLUSTERED";
        if (isUnique) {
          indexType = `UNIQUE ${indexType}`;
        }
        const columnNames = columns.join(", ");
    
        const request = new sql.Request();
        const query = `CREATE ${indexType} INDEX ${indexName} ON ${schemaName}.${tableName} (${columnNames})`;
        await request.query(query);
        
        return {
          success: true,
          message: `Index [${indexName}] created successfully on table [${schemaName}.${tableName}]`,
          details: {
            schemaName,
            tableName,
            indexName,
            columnNames,
            isUnique,
            isClustered
          }
        };
      } catch (error) {
        console.error("Error creating index:", error);
        return {
          success: false,
          message: `Failed to create index: ${error}`,
        };
      }
    }
  • Defines the input schema for the create_index tool, specifying parameters like schemaName, tableName, indexName, columns, isUnique, and isClustered.
    inputSchema = {
      type: "object",
      properties: {
        schemaName: { type: "string", description: "Name of the schema containing the table" },
        tableName: { type: "string", description: "Name of the table to create index on" },
        indexName: { type: "string", description: "Name for the new index" },
        columns: { 
          type: "array", 
          items: { type: "string" },
          description: "Array of column names to include in the index" 
        },
        isUnique: { 
          type: "boolean", 
          description: "Whether the index should enforce uniqueness (default: false)",
          default: false
        },
        isClustered: { 
          type: "boolean", 
          description: "Whether the index should be clustered (default: false)",
          default: false
        },
      },
      required: ["tableName", "indexName", "columns"],
    } as any;
  • src/index.ts:93-93 (registration)
    Instantiates the CreateIndexTool instance used throughout the server.
    const createIndexTool = new CreateIndexTool();
  • src/index.ts:115-119 (registration)
    Registers the createIndexTool in the list of available tools returned by ListToolsRequestHandler.
    server.setRequestHandler(ListToolsRequestSchema, async () => ({
      tools: isReadOnly
        ? [listTableTool, readDataTool, describeTableTool] // todo: add searchDataTool to the list of tools available in readonly mode once implemented
        : [insertDataTool, readDataTool, describeTableTool, updateDataTool, createTableTool, createIndexTool, dropTableTool, listTableTool], // add all new tools here
    }));
  • src/index.ts:138-140 (registration)
    Dispatches calls to the create_index tool by invoking its run method in the CallToolRequestHandler switch statement.
    case createIndexTool.name:
      result = await createIndexTool.run(args);
      break;
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool creates an index, implying a write operation, but lacks details on permissions required, whether the operation is reversible, potential impacts on database performance, or error handling. This leaves significant gaps in understanding the tool's behavior.

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, direct sentence that efficiently conveys the core action and target without unnecessary words. It is front-loaded with the key information, making it easy for an agent to parse quickly.

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?

Given the complexity of a database index creation tool with no annotations and no output schema, the description is insufficient. It lacks details on behavioral traits (e.g., side effects, error conditions), usage context, and expected outcomes, making it incomplete for safe and effective tool invocation.

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 description coverage is 100%, with all parameters well-documented in the input schema (e.g., columns, indexName, isClustered). The description adds no additional parameter semantics beyond what the schema provides, so it meets the baseline for adequate but not enhanced coverage.

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 action ('creates an index') and target ('on a specified column or columns in an MSSQL Database table'), making the purpose evident. However, it does not differentiate from sibling tools like create_table or update_data, which also modify database structures, leaving room for ambiguity in tool selection.

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. For instance, it does not mention prerequisites (e.g., table must exist), performance implications, or when to choose indexing over other database operations, leaving the agent without context for appropriate usage.

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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